IBM SPSS Data Collection Survey Reporter User s Guide

Transcription

1 IBM SPSS Data Collection Survey Reporter User s Guide

2 Note: Before using this information and the product it supports, read the general information under. This edition applies to IBM SPSS Data Collection Survey Reporter and to all subsequent releases and modifications until otherwise indicated in new editions. Adobe product screenshot(s) reprinted with permission from Adobe Systems Incorporated. Microsoft product screenshot(s) reprinted with permission from Microsoft Corporation. Licensed Materials - Property of IBM Licensed Materials - Property of IBM Copyright IBM Corporation 2000, 2011 Licensed Materials - Property of IBM Copyright IBM Corporation 2000, 2011 U.S. Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp.

3 Preface Welcome to the IBM SPSS Data Collection Survey Reporter User s Guide. This guide provides information on using the IBM SPSS Data Collection Survey Reporter application. For information about installing the product, see the IBM SPSS Data Collection Desktop Installation Guide. Adobe Portable Document Format (.pdf) versions of the guides are available on the IBM SPSS Data Collection Desktop CD-ROM. Viewing and printing the documents requires Adobe Reader. If necessary, you can download it at no cost from Use the Adobe Reader online Help for answers to your questions regarding viewing and navigating the documents. Notice: IBM SPSS Data Collection offers many powerful functions and features for use in the business of our customers. IBM is not responsible for determining the requirements of laws applicable to any licensee s business, including those relating to Data Collection Program, nor that IBM s provision of (or any licensee s receipt of) the Program meets the requirements of such laws. All licensees shall comply with all laws applicable to use and access of the Program, whether such use or access is standalone or in conjunction with any third party product or service. About IBM Business Analytics IBM Business Analytics software delivers complete, consistent and accurate information that decision-makers trust to improve business performance. A comprehensive portfolio of business intelligence, predictive analytics, financial performance and strategy management, andanalytic applications provides clear, immediate and actionable insights into current performance and the ability to predict future outcomes. Combined with rich industry solutions, proven practices and professional services, organizations of every size can drive the highest productivity, confidently automate decisions and deliver better results. As part of this portfolio, IBM SPSS Predictive Analytics software helps organizations predict future events and proactively act upon that insight to drive better business outcomes. Commercial, government and academic customers worldwide rely on IBM SPSS technology as a competitive advantage in attracting, retaining and growing customers, while reducing fraud and mitigating risk. By incorporating IBM SPSS software into their daily operations, organizations become predictive enterprises able to direct and automate decisions to meet business goals and achieve measurable competitive advantage. For further information or to reach a representative visit Technical support Technical support is available to maintenance customers. Customers may contact Technical Support for assistance in using IBM Corp. products or for installation help for one of the supported hardware environments. To reach Technical Support, see the IBM Corp. web site at Be prepared to identify yourself, your organization, and your support agreement when requesting assistance. Licensed Materials - Property of IBM Copyright IBM Corporation 2000, 2011 iii

4 Contents 1 Survey Reporter 1 WelcometoIBMSPSSDataCollectionSurveyReporter... 1 What snewinibmspssdatacollectionsurveyreporter Getting Started 5 Opening a SurveyDataFile... 5 Moving Around The IBM SPSS Data Collection Survey Reporter Window and Displaying Previews 7 Displaying ResultsandSavingYourWork...11 Creating Crosstabulations...13 Changing the CellContents...16 Adding a Filter...17 Changing the ContentofRowsandColumns...19 Creating ProfilesofRespondentData...22 Publishing YourResults The IBM SPSS Data Collection Survey Reporter User Interface 27 StartingIBMSPSSDataCollectionSurveyReporter...27 OpeningSurveyDataFiles...27 OpeningandSavingTableDocuments...29 OpeningTableDocumentsfromOtherApplications...30 CreatingNewTableDocuments...31 AdvancedDialogBox...31 TheIBMSPSSDataCollectionSurveyReporterWindow...32 TheIBMSPSSDataCollectionSurveyReporterMenus...32 TheIBMSPSSDataCollectionSurveyReporterToolbarButtons...35 Changing the Layout of the IBM SPSS Data Collection Survey Reporter Window FindingTablesorVariables...39 Undoing and Redoing Actions in IBM SPSS Data Collection Survey Reporter TheTablesPane...41 FindingTables...42 RenamingTables...42 OrganizingTables...43 TheVariablesFoldersPane...43 FindingVariables...45 iv

5 RenamingVariables...45 OrganizingVariables...46 SortingVariables...46 HidingVariables...47 PrintingVariables...48 TheVariablePreviewPane...49 DisplayingVariablePreviews...49 DocumentationandAdditionalResources...50 UsingtheOnlineHelp...50 NavigatingtheOnlineHelp...50 SearchingforInformation...51 PrintingInformation...53 UsingtheToolbar...54 NavigatingUsingtheKeyboard Creating tables 58 Creatingatable...59 Creatingmultipletableswiththesametopvariable...60 Switchingthetopandsidevariablesinatable...60 Addingandnestingvariables...61 Creatingtablesusinggridvariables...63 CreatingSummaryStatisticorSummaryMeanstables...65 SummaryStatisticTabledialogbox...67 CreatingSummaryMeanstables...69 Copyingatable...71 Viewingandcopyingthetablescript...72 Deletingatable...72 Bulkupdatingtabledefinitions...75 Advancedtabledefinitions...77 ditingatabledefinitionusingthetablesyntaxpane...77 Copyingtablesyntax...78 xample: Creating table definitions using non-categorical variables Changing Cell Contents 80 AddingandRemovingCellContents...81 CountsandUnweightedCounts...81 Percentages...83 v

6 Indices...87 SummaryStatisticsofNumericVariables...87 xpectedvaluesandresiduals Filtering Your Results 92 CreatingaFilter...92 ditingafilter...93 DeletingaFilter...94 SavingaFilter...95 ApplyingaFilterVariabletoAnotherTable...95 SettingtheLevelforaFilter...97 Bulkupdatingtablefilters...97 TableFilters...99 CategorySelection...99 GlobalFilters IBMSPSSDataCollectionGlobalFilters InterviewFilters ChanginganInterviewFilter FilterConditions SettingupConditionsforSingleResponseVariables SettingupConditionsforMultipleResponseVariables SettingupConditionsforNumericVariables SettingupConditionsforTextVariables SettingupConditionsforBooleanVariables SettingupConditionsforDateVariables SettingupConditionsforCategoricalGridVariables AdvancedFilterConditions AddingMultipleConditionstoaFilter GroupingFilterConditions ditingafilterusingthefiltersyntaxpane xamples:creatingcomplexfiltersusingthefiltersyntaxpane ChangingtheFilterDetailsinTableHeaders Using variables 113 Variabletypeoverview Categoricalvariables Numeric variables vi

7 Textvariables Loopsandgrids Booleanvariables Blocksandcompounds ditingvariables Changingthedescriptionforavariable Changingthedescriptionforacategory Changingthevariabledescriptionlanguage Changingtheorderofcategoriesinavariable Combiningcategories Creatingnets Combiningcategoriesinagrid Creatingsummarizedgrids Creatingbands Creatingacategorybasedonanothervariable Creatingacategorybasedonothercategories Addingsummarystatisticstoanumericvariable Addingsummarystatisticstoacategoricalvariable Addingsummarystatisticstoagrid Displayingasnapshotofvaluesforcategoriesinavariable Addingtextrowstotables Removingcategoriesfromavariable Creatingnewvariables Savingavariablewithanewname Copyingavariable Creatingavariablefromthesideortopofatable Mergingvariables Advancedvariabledefinitions Deletingvariables Deletingchangestovariables ditvariabledialogbox ditvariabledialogbox:propertiespane ditvariabledialogbox:scriptpane SaveVariableAs InsertCategoriesdialogbox InsertBandsdialogbox AddFactorsdialogbox Settingthenumberofresponsesinavariable dittablevariabledialogbox NewVariabledialogbox CreateNewVariableBasedOndialogbox Simplecategorization vii

8 Derivedvariablecreationfordatabasequestions Databasecategorization Base Rows and Columns 182 CalculationoftheBase WorkingwithBuilt-inBases xcludinginformationfromthebase HidingtheBase Applying Statistical Tests 188 RequestingStatisticalTests ModifyTableStatisticsDialogBox ToAddorRemoveaStatisticalTest To Add a Paired PreferenceTest ToViewDiagnosticsInformationforStatisticalTests Chi-Square Test xample of the Chi-SquareTest xampleoffisher sxacttest DetailsandRestrictionsoftheChi-SquareTest Statistical FormulafortheChi-SquareTest ColumnProportionsTest xamplesofthecolumnproportionstest Details and RestrictionsoftheColumnProportionsTest StatisticalFormulafortheColumnProportionsTest Column Means Test The Least SignificantDifference xamplesofthecolumnmeanstest xampleshowingtheleastsignificantdifferencecolumn Details and RestrictionsoftheColumnMeansTest StatisticalFormulafortheColumnMeansTest StatisticalFormulafortheLeastSignificantDifferenceTest NetDifferenceTest xampleofthenetdifferencetest DetailsandRestrictionsoftheNetDifferenceTest Statistical FormulafortheNetDifferenceTest PairedPreferenceTest xamplesofthepairedpreferencetest viii

9 DetailsandRestrictionsofthePairedPreferenceTest StatisticalFormulaforthePairedPreferenceTest ProductDifferenceTest xampleoftheproductdifferencetest DetailsandRestrictionsoftheProductDifferenceTest T-testTest xampleofthet-testtest DetailsandRestrictionsoftheT-testTest StatisticalFormulafortheT-testTest AddingaStatisticalTest SortingbyColumnSignificance AddingaPairedPreferenceTestoraNetDifferenceTest AddingaProductDifferenceTest AddDifferenceAttributes DisplayingDetailedStatisticalOutput DiagnosticsInformation DiagnosticsInformation:Chi-SquareTest DiagnosticsInformation:CellChi-SquareTest DiagnosticsInformation:ColumnProportionsTest DiagnosticsInformation:ColumnMeansTest DiagnosticsInformation:NetDifferenceTest DiagnosticsInformation:PairedPreferenceTest pvalues WeightedDataandtheffectiveBase DisplayinganffectiveBaseonaWeightedTable OverlappingData HierarchicalData SelectingColumnstoTest SettingtheSignificanceLevels MinimumBaseandSmallBaseValuesinStatisticalTests Applying Weighting 260 ShowingtheUnweightedBaseinWeightedTables AddingWeightingtoaTable OverridingTableWeighting ix

10 11 Tabulating Hierarchical Data 264 TheHierarchicalViewandtheFlatView ChangingtheView UsingTheVariablesPanewithHierarchicalData SettingtheTableGenerationLevel xamplesshowingresultsgeneratedatdifferentlevels xample Showing Summary Statistics of a Numeric Variable in Cell Contents UnderstandingGridTables TheBaseinGridTables TabulatingGridandLoopSlices FilteringHierarchicalData TheHouseholdSample Access Settings for Files on the Server 291 AccessLevelsinIBMSPSSDataCollectionSurveyReporter ViewingUnweightedData Versions 294 xampleusingmultipleversions Creating Profile Tables 296 CreatingaProfileTable SavingProfileData Presenting Your Results 298 SortingTables SortingaTable SortingTablesWithMultipleAddedorNestedVariables SortingCategoriesinNets SortingSpecialItems x

11 SortingGridTables HidingRows,Columns,andCells HidingaRoworColumn HidingCells ChangingHeadersandFooters AddingHeadersandFooters AddingFormattingtoHeadersandFooters AddingHypertextLinksandImagestoHeadersandFooters AddingNotestoHeadersandFooters MovingorDeletingHeadersandFooters HeaderandFooterPositions HTMLFormattingforHeadersandFooters GlobalHeadersandFooters DisplayingResultsinCharts DisplayingaChart HowDataisDisplayedinaChart ChartTypes ChangingTableProperties TableProperties:CellContents TableProperties:Display TableProperties:Weight TableProperties:Statistics TableProperties:Hide TableProperties:Level TableProperties:Sort TableProperties:HeaderandFooter TableProperties:Chart TableProperties:DefaultPropertiesDialogBox Publishing Your Results 354 PrintingResults xportingresults nabling security access for Microsoft xcel, Word, and PowerPoint exports xporttablesdialogbox HTMLxports Microsoftxcelxports MicrosoftPowerPointxports MicrosoftWordxports Textxports xportingtablesusingmicrosoftxcelstyles xi

12 xportingchartsusingmicrosoftxcelcustomcharttypes UsingHTMLFormattinginCategoryDescriptions FormattingtheOutputinMicrosoftWord WorkingwithMicrosoftWordTemplates ChangingtheMicrosoftWordxportOrientationtoLandscape Changing the Headers and Footers Used in the Table of Contents PositioningtheOutputinaMicrosoftWordxportFileUsingBookmarks WorkingwithMicrosoftWordStyles TheDefaultMicrosoftWordxportStyles CreatingandModifyingMicrosoftWordParagraphStyles xportingdata xportdatadialogbox:generaltab xportdatadialogbox:variablestab xportdatadialogbox:filtertab DistributingDataandResults Transferring Table Documents Between IBM SPSS Data Collection Survey Reporter and OtherApplications SupplyingSourceFilesandResultstoCustomers ChangingtheLogoDisplayedintheResultsPane Converting IBM SPSS Quanvert Table Specification (.qsf) files to Data Collection Table Document (.mtd) files Customizing IBM SPSS Data Collection Survey Reporter 399 Customizing TableDocumentTemplates Creating a TableDocumentTemplate CreatingaTemplateFromaTableDocument RemovingaTemplate CustomizingtheFormatofYourResults ditingstylesheets ditingstylesheets:xample Style Sheet Settings ChangingFileProperties FileProperties:GeneralTab File Properties: DataTab FileProperties:AdvancedTab Changing IBM SPSSDataCollectionSurveyReporterOptions Options: General Tab Options:DisplayTab xii

13 Options:SizeandLayoutTab Options:FileLocationsTab IBM SPSS Data Collection Publish Assets Utility Reference 422 TableSpecificationSyntax TableandAxisSyntax lementlistsyntax lementsyntax lementpropertysyntax Languages(3-CharacterCodes) NamingConventions FunctionList Multi-wavestudies RoundinginIBMSPSSDataCollectionSurveyReporter FormulaeforCellContents FormulaeforStatisticalTests StatisticalFormulafortheChi-SquareTest StatisticalFormulafortheColumnProportionsTest StatisticalFormulafortheColumnMeansTest StatisticalFormulafortheLeastSignificantDifferenceTest StatisticalFormulafortheNetDifferenceTest StatisticalFormulaforthePairedPreferenceTest StatisticalTestsComparedtoIBMSPSSStatistics StatisticalTestsComparedtoIBMSPSSQuantumandIBMSPSSQuanvert Troubleshooting, Tips and Hints 460 FrequentlyAskedQuestions IBMSPSSDataCollectionSurveyReporterinOtherLanguages Troubleshooting Accessibility Guide 466 KeyboardNavigation Accessibility for the Visually Impaired Accessibility for Blind Users xiii

14 SpecialConsiderations SpecialConsiderations:DialogBoxes SpecialConsiderations:InterferencewithOtherSoftware Glossary 469 Index 473 xiv

15 Survey Reporter Chapter 1 Welcome to IBM SPSS Data Collection Survey Reporter This User s Guide shows you how to use IBM SPSS Data Collection Survey Reporter The following table provides a summary of the main sections of this guide. What s New Getting Started The IBM SPSS Data Collection Survey Reporter User Interface Creating tables Changing Cell Contents Filtering Your Results Using variables Base Rows and Columns Applying Statistical Tests Applying Weighting Tabulating Hierarchical Data Versions Creating Profile Tables Presenting Your Results Publishing Your Results Customizing IBM SPSS Data Collection Survey Reporter Reference Troubleshooting, Tips and Hints Accessibility Guide A summary of the new features available in each release. A step-by-step guide to help you find your way around IBM SPSS Data Collection Survey Reporter and learn how to access survey data and how to create, display, format, and export your results. Details of how to navigate around the Survey Reporter window and work with some of the main features of the user interface. Information on creating and editing your tables. Details of the cell contents that you can include in tables. Details of how to filter the data in your tables. Details of the types of variable that you can include in tables, and information on how to add variables to tables, edit existing variables, and create new ones. Information about how the values in base rows and columns are calculated and how to work with bases. Information on adding statistical tests to tables. Information on adding weighting to tables. Information on hierarchical data and how Survey Reporter handles it. Information on how to work with versioned data. Details of how to create profiles. Topics on how to change the way in which your tables are displayed, including sorting tables, adding headers and footers, and displaying data in chart format. Information on how to print your results or export them to a variety of file formats, including Microsoft xcel, Word, and PowerPoint. Information on how to configure Survey Reporter to tailor it to your requirements. Reference information about Survey Reporter. Information to help you overcome problems and recover from errors, as well as tips and tricks to increase performance. Information about accessibility in the Survey Reporter user interface. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

16 2 Chapter 1 What s New in IBM SPSS Data Collection Survey Reporter Virtual directory, session engine, and Web service registration. During the product installation, you are presented the option for configuring multiple virtual directories, session engines, and Web services. Configuring multiple virtual directories, that run simultaneously, provides for optimum load balancing within a cluster. When any of the following features are selected during installation, youarepresentedwiththeinterviewerserver Administration Virtual Directory Configuration dialog during installation: Accessories Service Phone Interviews Remote Administration Survey Tabulation Survey Reporter Server dition Author Server dition Configuring multiple session engines allows you to better utilize the memory on each IBM SPSS Data Collection Interviewer Server machine. When you select to install the Interview Service feature, the Interview Session ngine Configuration dialog displays during installation. Configuring multiple Web services to run on a single machine allows you to better utilize the memory on each Web server machine. When you select to install the Web Service feature, the Interview Web Service Configuration dialog displays during installation. Refer to the Virtual directory, session engine, and Web service registration section in the IBM SPSS Data Collection Server Installation Guide for more information. Integration with IBM SPSS Collaboration and Deployment Services Repository.IBM SPSS Data Collection provides support for storing and retrieving.mtz packages (zip archives) to a IBM SPSS Collaboration and Deployment Services Repository. A package is an executable element of IBM SPSS Data Collection. An.mtz package contains a primary.mtd file and a configuration file for the.mtd. IBM SPSS Collaboration and Deployment Services is used as a job scheduling and configuration platform. User-configured script items are exposed to IBM SPSS Collaboration and Deployment Services, but IBM SPSS Collaboration and Deployment Services will not execute any part of a Data Collection script. User-configured items include parameters and store locations, access permissions, and output file properties. IBM SPSS Data Collection Survey Reportersupports the following integration with the IBM SPSS Collaboration and Deployment Services Repository: Script Packager component. The component provides support for generating deployable.mrz,.dmz, andmtz packages (zip archives) for the purpose of integration with IBM SPSS Collaboration and Deployment Services Repository. Refer to the Script Packager Component

17 3 Survey Reporter Object Model section in the IBM SPSS Data Collection Developer Library for more information. Data Collection xecution Server. Provide the web services to process the zip archive packages and associated configuration files. The server executes and returns the output variables and output files via a web service response. The server also supports IBM SPSS Collaboration and Deployment Services job step cancellation. Data Collection IBM SPSS Collaboration and Deployment Services example. The Data Collection IBM SPSS Collaboration and Deployment Services example provides an IBM SPSS Data Collection integration scenario with IBM SPSS Collaboration and Deployment Services. The example is stored in the [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\DDL\Scripts\Data Management\Collaboration Deployment Services directory. Refer to TheDataCollection Collaboration and Deployment Services example for more information. Refer to the Introduction to IBM SPSS Collaboration and Deployment Services Repository integration section in the Data Collection Developer Library for more information. Support for reserved names and keywords in metadata. Data Collection now provides full support for SQL and mrscript reserved names and keywords in metadata variables. In previous releases, the use of reserved SQL keywords could cause issues when using the IBM SPSS Data Collection Data Model to query data for processes such as DMOM; the use of reserved mrscript keywords could cause syntax errors when referenced within a routing script. Refer to the Reserved Keywords and Keyword Summary topics in the Data Collection Developer Library for more information. Bulk updating table specifications. You can now bulk update the banners (top axis) and side axis for multiple tables. When you select multiple tables, that have same side or top axis, the side and top axes will display as a single table. Changes applied to side or top axis design controls will apply for all selected tables. For more information, see the topic Bulk updating table definitions in Chapter 4 on p. 75. Bulk updating table filters. You can now bulk update the filters for multiple tables. When you select multiple tables, that have the same filters, the selected tables will display as a single table. xpression and level changes for the displayed filter will apply to all selected tables. For more information, see the topic Bulk updating table filters in Chapter 6 on p. 97. Converting Quanvert Table Specification (.qsf) files to Data Collection Table Document (.mtd) files. You can use the IBM SPSS Quanvert to Data Collection Table Document Files Conversion wizard to convert Quanvert Table Specification (.qsf) files to Data Collection Table Document (.mtd) files. When you open a Quanvert Table Specification (.qsf) file in Survey Reporter, the wizard automatically displays and walks you through the conversion process. For more information, see the topic Converting IBM SPSS Quanvert Table Specification (.qsf) files to Data Collection Table Document (.mtd) files in Chapter 17 on p. 398.

18 4 Chapter 1 Shortcuts for the bulk conversion of Count, Sum, and Mean tables. Menu and toolbar shortcuts have been added to aid in the bulk conversion of selected tables to Count, Sum, and Mean tables. When you select one or more tables, and there is only one numerical variable selected in the variable list window, you can select the following options: Summarize by count. Available under the Tables menu and on the Tables toolbar, this option converts the selected table(s) to count tables based on the selected variable. Summarize by sum. Available under the Tables menu and on the Tables toolbar, this option converts the selected table(s) to sum tables based on the selected numeric variable. Summarize by mean. Available under the Tables menu and on the Tables toolbar, this option converts the selected table(s) to mean tables based on the selected numeric variable. xporting data. You are now provided the option of selecting which variables should be exported for the axis variable. For more information, see the topic xport Data Dialog Box: Variables Tab in Chapter 16 on p x64 64-bit support. x64 64-bit editions are now provided for the Data Collection applications (note that IBM SPSS Data Collection Author Server dition and IBM SPSS Data Collection Survey Reporter Server dition are only provided as x86 32-bit). Refer to the appropriate Data Collection installation guide for more information. Fix pack and hotfix information. You can now view information regarding which fix packs and hotfixes are installed via the application s Help menu. Help > About Survey Reporter... > Details...

19 Getting Started Chapter 2 ThetopicsinthissectionwalkyouthroughgettinginandoutofIBM SPSS DataCollection Survey Reporter, navigating around the Survey Reporter window, and carrying out some common tasks including creating and exporting tables. ach topic contains links to topics with further details. It is recommended that you read these topics in order and, if possible, try following the examples using the sample survey data. The tables in these topics use the Museum XML sample survey data, which comes with the IBM SPSS Data Collection Developer Library. If you do not have access to this sample, you may want to try following the examples using your own survey data to create similar tables. Topics in this section 1. Opening a Survey Data File 2. Moving Around The IBM SPSS Data Collection Survey Reporter Window and Displaying Previews 3. Displaying Results and Saving Your Work 4. Creating Crosstabulations 5. Changing the Cell Contents 6. Adding a Filter 7. Changing the Content of Rows and Columns 8. Creating Profiles of Respondent Data 9. Publishing Your Results Opening a Survey Data File Once you have installed IBM SPSS Data Collection Survey Reporter, you can open it from the Windows Start menu. Choose: Programs > IBM SPSS Data Collection > IBM SPSS Data Collection Survey Reporter > IBM SPSS Data Collection Survey Reporter The Survey Reporter window appears. In Survey Reporter, you can work with survey data from a number of different file formats, including SPSS SAV files, IBM SPSS Quanvert databases, relational Data Collection databases, and Data Collection XML data files. The survey data file is opened read-only, and Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

20 6 Chapter 2 all the work that you do is saved in the form of a table document (.mtd) file, which references the survey data file. In most cases, rather than open the data file directly, you open a metadata (.mdd) file that refers to the data file and tells Survey Reporter how to read the data. Open a survey data file From the menu, choose: File > Open Use the Open dialog box to browse to the Museum sample survey (or one of your own survey data files). By default, the Museum survey data is installed with the IBM SPSS Data Collection Developer Library in [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\DDL\Data\XML. Select the metadata (Museum.mdd) file and choose Open. The survey data file opens, and a list of all the variables in the file appears in the Variables pane. Figure 2-1 The Variables pane As well as opening the survey data file, Survey Reporter creates a new table document (mtd) file, in which you can save the results of your analysis of the survey data. This means that your survey data file is not affected by any changes that you make using Survey Reporter, as all changes are saved in the table document file. At the moment, this file has no name, as you can see from the title bar and the top level of the Tables pane, which say Untitled. In a later topic, we will save the file and give it a name. For now, we will add a description of the project to the file. From the menu, choose File > Properties In the File Properties dialog box, enter the description Museum of the Living World Visitor Survey in the Description field, and choose OK to close the dialog box. The description is displayed in the Design pane, and will also appear when you display results. To exit Survey Reporter once you have finished working through these examples, choose: File > xit

21 7 Getting Started If you have any unsaved changes, you are prompted to save them in a table document (.mtd) file. Moving Around The IBM SPSS Data Collection Survey Reporter Window and Displaying Previews The IBM SPSS Data Collection Survey Reporter window is divided into a number of areas. On the left of the window are the Tables pane, which displays a list of all the tables you create, and the Variables pane, which displays a list of all the variables in your survey data. In the center are the Design, Filter, and Results panes, where you define how you want tables to appear and display the results. As you work with Survey Reporter, you may find it useful to rearrange the window by resizing or switching off tabs that you are not using. You can also move menus, toolbars, and individual tabs around in the window. Try rearranging the window: Resize the Tables pane If you find that there is not enough space in some areas of the screen, you can change the size of different areas, for example, the Tables pane. Place the mouse pointer between the Variables pane and the Tables pane, and click and drag the edge upwards. Figure 2-2 Resizing the Tables pane

22 8 Chapter 2 Display Previews of Variables You can display a snapshot of the data values in a variable, before you add it to a table: Right-click a variable, for example, age, in the Variables pane: Figure 2-3 Select age From the context menu, choose Generate Variable Preview. The Variable Preview pane appears, with a summary of the values in each category of the variable. Depending on the type of variable, you can display a chart, a table, or the original question, by clicking the relevant tab at the bottom of the pane: Figure 2-4 Selecting a table preview for the age variable (Not all options are available for all types of variable). When you want to close the pane, choose the X button on the title bar of the pane, or press Alt+9 (pressing Alt+9 again reopens the pane).

23 9 Getting Started Dock the Variable Preview pane A number of panes, including the Variable Preview pane, the Tables pane and the Variables pane, can be moved around the window and displayed either as floating panes or as docked panes. Try docking the Variable Preview pane beneath the Variables pane: First, unlock the window settings so that you can move the toolbar. From the menu, choose: Tools > Options Choose the Size and Layout tab and select the Allow docking and undocking of window panes check box, then choose OK. Place the mouse pointer on the title bar of the Variable Preview pane, and click and drag the pane. You will see that an outline appears around the pane to indicate where it will be placed when you release the mouse. As you drag the pane around the screen, this outline jumps to the nearest available location to place it. Drag the pane to the bottom left of the screen, then, when the outline appears beneath the Variables pane, release the mouse button.

24 10 Chapter 2 Figure 2-5 Moving the Variable Preview tab The Variable Preview pane appears in the new location. Note: It can take a few attempts to get thepanetogowhereyouwantitto. Move the Tables toolbar Place the mouse pointer at the left of the Tables toolbar. The cursor changes to a four-pointed arrow: Figure 2-6 Selecting the Tables toolbar Click and drag the toolbar and drop it in the middle of the window: Figure 2-7 The Tables toolbar undocked You can leave the toolbar floating on top of the window, or drag it to the top, side or bottom of thewindow,anddropittodockitinposition. Try moving some of the other panes and toolbars around the window. The changes you make will be remembered when you close Survey Reporter and reopen it.

25 11 Getting Started Lock Changes In Place If you are happy with your changes, you can lock the settings of the docked windows and toolbars when you have finished, so that you do not make accidental changes. Choose: Tools > Options Choose the Size and Layout tab and deselect the Allow docking and undocking of window panes check box, then choose OK. Restore the Layout If you do not want to keep the changes you have made, you can restore the layout settings to the defaults supplied with Survey Reporter. From the menu, choose: View > Restore Default Layout At the prompt, choose Yes. The screen reverts to the original layout. Displaying Results and Saving Your Work There are a number of ways of creating tables to display different views of your survey data. The easiest is to add the variables to the table area in the Design pane. Display the results for a single variable In the Variables pane, select the found_way variable. Tip: You can move quickly to a variable in the Variables pane by typing the first letters of its name until you reach the one you want. Choose the Add button on the Side area of the Design pane: Figure 2-8 Adding a variable to the side of the table

26 12 Chapter 2 Thevariableappearsonthesideofthetable: Figure 2-9 Adding a variable to the side of the table The table has the automatically generated description Table1. Click in the Table Description field and replace this with the description How respondent found way. You have now finished setting up the table, and all you need to do is generate the results. Choose the Results pane. Figure 2-10 Selecting the Results pane Tip: You can also press the F5 key, or select the Generate Results button on the toolbar: Figure 2-11 Generate results button IBM SPSS Data Collection Survey Reporter generates and displays the results. The table shows the number of respondents who gave a response in each category, and the percentage of the total that each category represents.

27 13 Getting Started Figure 2-12 Frequency table of found_way Save your results From the menu, choose: File > Save or press Ctrl+S. In the Save dialog box, browse to a folder where you want to save your results. In the File Name field, enter a name for the file, for example, Museum Survey Results, andchoose Save. The file is saved with the file extension.mtd. Creating Crosstabulations The previous topic showed how to create a simple table showing the frequency of responses in each category of a variable. This topic shows how to crosstabulate two variables. Crosstabulate age and gender From the menu, choose: Tables > New > Table Tip: You can also press Ctrl+T, or select the New table button on the toolbar: Figure 2-13 New table button

28 14 Chapter 2 In the Variables pane, locate the age variable: Figure 2-14 Selecting the age variable Click and drag the age variable onto the Add button in the Side area of the Design pane: Figure 2-15 Adding a variable to the side of the table Thevariableappearsonthesideofthetable: Figure 2-16 Adding a variable to the side of the table Tip: You can also press Ctrl+Alt+S to add the selected variable to the side.

29 15 Getting Started In the same way, select the gender variable and add it to the top of the table (or use Ctrl+Alt+T): Figure 2-17 Adding a variable to the top of the table Tip: If you add a variable by mistake, press Ctrl+Z to undo the change. Replace the description Table2 with Age by gender. This time, select the toolbar button to generate the results: Figure 2-18 Generate results button IBM SPSS Data Collection Survey Reporter generates the table and displays it in the Results pane. Figure 2-19 Table of age by gender

30 16 Chapter 2 In this example, the Base row shows how many respondents there are of each gender and the Base column shows how many respondents there are in each age group. The point where a row and a column intersect is called a cell, and in this table the cells show the number of respondents with the combined set of row and column characteristics. For example, the cell at the intersection of the years row and the Male column shows that there are 108 men age between 25 and 34 in the sample. To save the results, press Ctrl+S or use the menu option: File > Save The table document that you saved previously is updated to include the new table. Changing the Cell Contents If you look at one of the tables created in the previous topics, you can see that each cell of the table contains two figures. These are the default cell contents, namely counts (the number of respondents that satisfy the row and column conditions for each cell) and column percentages. The cell contents for each table are listed in the table footer. You can change the cell contents for any table to show the information that you are interested in. Remove column percentages from a table In the Tables pane, select the table you created in Creating Crosstabulations: Figure 2-20 Selecting a table From the menu, choose Tables > Properties Tip: You can also press F4, or choose the Table Properties button on the toolbar: Figure 2-21 Table Properties button The Table Properties dialog box appears, showing the Cell Contents tab. On the left of the tab is a list of all the types of cell contents that you can use in a table. On the right are the two default items, Counts and Column Percentages. Select Column Percentages in the Included in cells list on the right of the dialog box, and use the << button to remove it from the list of items.

31 17 Getting Started Figure 2-22 Removing column percentages Choose OK to close the dialog box. The table is regenerated automatically to display the updated results (if the Results pane is not selected, select it or press F5 to generate the results). The table now contains only counts. Figure 2-23 Table of age by gender showing only counts Finally, press Ctrl+S to save the updated table in the table document. Adding a Filter You can apply filters to your data, so that only those cases meeting certain conditions are included in the results. In this example, we will make a copy of the table of age by gender, and filter out all respondents of 16 years of age and under; that is, those who selected the years category in the survey question: To which age group do you belong? Create a filter to exclude respondents aged 16 and under In the Tables pane, select the table you created in Creating Crosstabulations: Figure 2-24 Selecting a table

32 18 Chapter 2 From the menu, choose dit > Copy then dit > Paste Tip: You could also press Ctrl+C followed by Ctrl+V. A new table called Copy of Age by gender is added to the Tables pane. The new table contains all the information from the original table, including the change to the cell contents. In the Design pane, change the tabledescriptiontosayage by gender, filtered. Select the Filter pane: Figure 2-25 The Filter pane In the Filter description field, enter the text: xcludes 16 and under. This description will appear as a header in the Results pane. In the Variables pane, select the age variable: Figure 2-26 Selecting the age variable Drag the variable onto the filter area (or you can use Ctrl+Alt+F): Figure 2-27 adding a filter variable The variable is added to the Filter pane. As this is a categorical variable, a list of the categories appears to the right of the category name. To the left is a drop-down list. Select Includes none of these from the list, then select the years check box: Figure 2-28 adding a filter condition

33 19 Getting Started This is all you need to do to create the filter. It is automatically applied to the table when you click away from the Filter pane or generate the results. To generate the results, press F5. This is the resulting table: Figure 2-29 Table of age by gender, year age group filtered out Notice that the 38 respondents aged have been removed from the table, and that the original table base value of 602 has been reduced to 564. Finally, press Ctrl+S to save the new table in the table document. Changing the Content of Rows and Columns You can change the content of individual rows and columns in the table, for example, to remove categories or create new categories based on existing ones. In this topic we will start with a table containing the age and gender variables, edit the category descriptions for the gender variable, then reduce the number of rows in the age variable by combining the existing categories into three new ones. Firstofall,createanewtableandaddage to the side and gender to the top, as shown in the Creating Crosstabulations topic. Change category descriptions On the Design pane, select the gender variable.

34 20 Chapter 2 Figure 2-30 Selecting the gender variable From the menu, choose: Variables > dit Table Variable Tip: You could also double-click the variable on the Design pane (not the Variables pane). The dit Table Variable window appears, with details of all the categories that appear on the table for the selected variable. Because you are editing the variable on the table, the changes you make apply only to that table and will not affect any other tables that use the variable (if you wanted the changes to apply to all tables, you would select the variable in the Variables pane, not in the Design pane). Figure 2-31 The dit Variable window Double-click Male in the Category descriptioncolumntoselectthetext. Change the text to say Men, then press nter to apply the change. In the same way, select the Female category description and change it to Women.

35 21 Getting Started Choose the Save and Close button to save your changes and close the dit Table Variable window. Combine categories On the Design pane, double-click the age variable. In the dit Table Variable window, use Shift+click to select the years, years, and years categories. From the Variables toolbar, choose Categories > Combine > Combine The three categories are combined into a single category with an automatically generated description. Change the description in the same way as for the gender variable, but this time, enter Young as the description. Inthesameway, combinethe25-34 years, years, and45-54 years categories, giving the new combined category a description of Middle. In the same way, combine the years and 65+ years categories, giving the new combined category a description of Old. The categories should now look like this: Figure 2-32 Combined categories Choose the Save and Close button. Replace the default description Table4 with Age (banded) by gender.

36 22 Chapter 2 Press F5 to update the results. The table appears as follows: Figure 2-33 Table of Age by Gender with renamed gender categories and age categories combined into Young, Middle and Old ach of the new categories contains the total number of respondents from the original categories that were combined to make it. Finally, press Ctrl+S to save the table in the table document. Creating Profiles of Respondent Data In addition to creating tables to analyze survey data, you can also create tables that simply display the responses to one or more questions for all respondents or for selected respondents. These tables are called profile tables. Profile tables are useful for getting a quick overview of the responses in a survey. For example, you may want to get a rough idea of the distances travelled by respondents who have visited the museum several times in the past year. Create a profile table From the menu, choose Tables > New > Profile or press Ctrl+R. In the Variables pane, select the visits12 variable, and drag it into the Profile area on the Design pane: Figure 2-34 Adding a variable to a profile table In the same way, select the distance variable and add it to the profile.

37 23 Getting Started Figure 2-35 Adding visits12 and distance to a profile table Tip: You can also press Ctrl+Alt+P to add the selected variable to the profile table. Replace the default profile description with Frequent visitors. Choose the Filter tab, and click and drag the visits12 variable to the Filter area. Select is greater than or equal to from the drop-down list, and type 5 in the text box. Figure 2-36 visits12 is greater than or equal to 5 Press F5 to generate the results. The profile table shows a list of the responses to the Number of previous visits in last 12 months and Distance from home to museum questions for all respondents who have visited the museum five or more times in the last 12 months. Figure 2-37 Profile table showing responses for visits12 and distance for respondents with more than 4 visits in last 12 months To see the table exactly as shown above, change the style by choosing Color Code from the drop-down list of style sheets in the tool bar. Note that all the other tables also change to use the new style. Finally, press Ctrl+S to save the profile table in the table document.

38 24 Chapter 2 Publishing Your Results When you have finished analyzing your results you can publish them in a variety of file formats by exporting from IBM SPSS Data Collection Survey Reporter. For example, you can export to a Microsoft xcel spreadsheet, Word document, or PowerPoint presentation. You can also export to an HTML file or to a plain text file. You can change the output format in various ways, depending on the type of file you are exporting to. For example, when you export to PowerPoint you can attach your own template to the slides. xport all tables to Microsoft xcel If it is not already open, open the file Museum Survey Results.mtd that you created previously. From the menu, choose: File > xport > Tables Tip: You can also choose the xport Tables button on the toolbar: Figure 2-38 xport Tables button The xport Tables dialog box appears. In the xport tables to drop-down list, select Microsoft xcel. Leave the other settings as they are, and choose the OK button. Survey Reporter opens Microsoft xcel and displays the tables, each in a separate worksheet. Charts are displayed in a separate worksheet after each table.

39 25 Getting Started Figure 2-39 Tables exported to xcel In xcel, choose File > Save and save the xcel file in a suitable folder. xport selected tables to Microsoft PowerPoint and attach a template In the Tables pane, use Ctrl+click to select the tables named Age by gender and Age (banded) by gender: Figure 2-40 Selecting tables using Ctrl+click From the menu, choose: File > xport > Tables The xport Tables dialog box appears. From the xport options, choose Selected tables. In the xport tables to drop-down list, select Microsoft PowerPoint, then choose the More >> button. Check the Apply PowerPoint template box, then choose the Browse button next to the field and use the Open dialog box to select a template (by default, PowerPoint templates are stored in

40 26 Chapter 2 subfolders under a Microsoft Office templates folder, for example, C:\Program Files\Microsoft Office\Templates\Presentation Designs, with the file extension.pot). When you have selected a template file, choose Open. Leave the other settings in the xport Tables dialog box as they are, and choose the OK button. Survey Reporter opens Microsoft PowerPoint and displays the results in the form of a chart, formatted using the template you selected (the example below uses the Pixel template available with PowerPoint 2003). Figure 2-41 Table of age by gender and age (banded) by gender, exported to PowerPoint In PowerPoint, choose File > Save and save the PowerPoint file in a suitable folder.

41 Chapter 3 The IBM SPSS Data Collection Survey Reporter User Interface This section explains how to start up IBM SPSS Data Collection Survey Reporter and open and save files, and provides an introduction to the main features of the Survey Reporter window and how to use them. Starting IBM SPSS Data Collection Survey Reporter You can start one or more instances of IBM SPSS Data Collection Survey Reporter from the desktop (having two instances open at the same time is useful if you want to copy tables from one table document to another). Starting IBM SPSS Data Collection Survey Reporter from the desktop From the Windows Start menu, choose: Programs > IBM Corp. > IBM SPSS Data Collection > Survey Reporter > Survey Reporter Starting IBM SPSS Data Collection Survey Reporter from IBM SPSS Data Collection Interviewer Server Administration From the Windows Start menu, choose: Programs > IBM Corp. > Data Collection > IBM SPSS Data Collection Interviewer Server Administration > Start Interviewer Server Administration After logging on to Interviewer Server Administration, navigate to the desired project and then click Survey Reporter near the bottom of the screen. When prompted if you want to run this application, click Run. The first time you launch Survey Reporter, required files will be downloaded to your machine. This may take several minutes to complete. xiting IBM SPSS Data Collection Survey Reporter From the Survey Reporter menu, choose: File > xit If you have any unsaved results, you are prompted to save them in a table document (.mtd) file. Opening Survey Data Files You can work with survey data from a large number of file formats. The survey data file is opened read-only, and all the work that you do is saved in the form of a table document (.mtd) file, which references the survey data file. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

42 28 Chapter 3 To open a survey data file From the menu, choose: File > Open Note that if you are running IBM SPSS Data Collection Survey Reporter via IBM SPSS Data Collection Interviewer Server Administration, you cannot open local files. The Open command is disabled, and you can only open files from the Interviewer Server Administration server (sometimes known as the Accessories server). To open a survey data file from the server From the menu, choose: File > Open from Interviewer Server Administration Note: The Survey Reporter application must be installed on the server prior to using the Open from Interviewer Server Administration feature. Use the Open dialog box to browse to the survey data file. This may be one of a number of different file types, depending on how your data has been set up. In some cases, rather than opening the survey data file directly, you open an associated metadata file. This is a file containing information about the survey data file. It enables Survey Reporter to understand the structure of the case data. If a metadata file exists for your survey data, it is recommended that you open the file using the metadata file rather than the case data file. Metadata files are usually stored in the same folder as the case data file, with the same file name, but with a file extension of.mdd. Alternatively, navigate to the file using Windows xplorer and drag and drop the survey data file (or the associated metadata file if one exists) onto the Survey Reporter window. (This does not applytothewebdeploymentofsurveyreporter.) Tip: You can also drag and drop a survey data file directly onto the Survey Reporter executable file in Windows xplorer to open Survey Reporter and the data file at the same time. (This does not applytothewebdeploymentofsurveyreporter.) When you open a survey data file, Survey Reporter also creates a new table document (.mtd) file in which to save the results of your analysis of the survey data. The original survey data file is not affected by the changes that you make using Survey Reporter. To reopen a file If you have recently opened a file (either a survey data file or a previously saved.mtd file), you can reopen it directly from the menu. Choose Files > Recent Files and select the file from the list.

43 The IBM SPSS Data Collection Survey Reporter User Interface 29 Opening and Saving Table Documents When you first open a survey data file, a new blank table document (.mtd) file is created. You can use this to save the results of your analyses in table or chart format. When working on a survey, you may want to create several table documents and switch between them. For example, in the Museum sample survey, there are two main groups of respondents those who were interviewed entering the museum and those who were interviewed leaving the museum. The two groups of respondents were asked different sets of questions. When analyzing the survey responses, you might decide to create three.mtd files one to analyze the responses to the questions put to the first group, one to analyze the responses to the questions put to the second group, and one to analyze the responses to the questions that were put to both groups. You can save table documents on your hard drive, on a shared drive to which you have access so that they are available to other users, or to the server. To open a table document From menu, choose: File > Open Note that if you are running IBM SPSS Data Collection Survey Reporter via IBM SPSS Data Collection Interviewer Server Administration, you cannot open local files. The Open command is disabled, and you can only open files from the server. To open a table from the server From the menu, choose: File > Open from Interviewer Server Administration Note: The Survey Reporter application must be installed on the server prior to using the Open from Interviewer Server Administration feature. Use the Open dialog box to browse to a previously saved table document, and choose Open. Survey Reporter opens the data survey file associated with the table document and displays any tables that have already been created. To open IBM SPSS Data Collection Survey Reporter with a table document You can also open Survey Reporter directly with a specific table document (.mtd): Navigate to the file using Windows xplorer and double-click the file to open Survey Reporter with that file. This automatically opens the associated survey data file, and displays any tables in the table document, as well as the variables in the associated data survey file. (

44 30 Chapter 3 Alternatively, if you have recently opened the file,youcanreopenitdirectlyfromthemenu. Choose Files > Recent Files and select the file from the list. To save a table document From the menu, choose File > Save IntheSavedialogbox,browsetoa folder where you want to save your results. In the File Name field, enter a name for the file and choose Save. When performing a Save As for a file that was opened from the server (Interviewer Server Administration), note that you can only save to the current project directory. Opening Table Documents from Other Applications To Open a Table Document in IBM SPSS Data Collection Survey Reporter You can open.mtd files created using IBM SPSS Data Collection Survey Reporter Professional or IBM SPSS Data Collection Survey Tabulation, either using the same or a different data source. For information on the differences between table documents in IBM SPSS Data Collection Survey Reporter and Survey Tabulation, see Transferring Table Documents Between IBM SPSS Data Collection Survey Reporter and Other Applications. From the IBM SPSS Data Collection Survey Reporter menu, choose Files > Open Table Document The file opens using the metadata and case data files in the same location as was specified in the script. If the files are not available in that location, the File Open dialog appears to enable you to choose the metadata file in the new location. To open the file with a different data source: From the IBM SPSS Data Collection Survey Reporter menu, choose Files > Advanced Choose the Open with Dataset button. Browse to the location of the data source and select the metadata file, then choose OK.

45 The IBM SPSS Data Collection Survey Reporter User Interface 31 Creating New Table Documents To Create a new table document For projects opened from IBM SPSS Data Collection Interviewer Server Administration, you can create a new table document directly from the File menu or the toolbar in both the Web and desktop deployments of IBM SPSS Data Collection Survey Reporter. The table document is based on the current Interviewer Server Administration project, and the current user has minimum permissions. From the menu, choose File > New or press Alt+F, N, or click the Create New Table Document icon on the toolbar. Advanced Dialog Box You can use the Advanced dialog box to save a copy of the current table document without the survey data file details, or reopen the file with a different data set. To display the Advanced dialog box, choose File > Advanced from the menu. Fields on the Advanced dialog box The Advanced dialog box is broken into two sections. The upper section allows you to save a copy of the current document without any data set references. It contains the following fields: Include table and profile results when saving. Select this option if you want to keep the results as well as the table and profile specifications. Copy To Local File... Click this button to save a copy of the document on your local workstation. Copy to IBM SPSS Data Collection Interviewer Server Administration... Clickthisbuttontosave a copy of the document to the server. The lower section of the Advanced dialog box allows you to reopen the current document with a different data set reference. It contains the following fields: Add new elements to edited variables. If you select this option, elements added in the dataset being opened will be added to the edited variables in the current document. Variables that have been edited on a table will not be updated. Note: Interviewer Server Administration does not distinguish between elements that were added in the current survey data file and those that were deleted in the new file you are opening. Therefore, in the latter case, selecting this option effectively restores the deleted elements.

46 32 Chapter 3 Open With Dataset... Clickthisbuttontoopenthefile with a new data set. You are prompted to select a survey data file. The IBM SPSS Data Collection Survey Reporter Window The IBM SPSS Data Collection Survey Reporter Menus The IBM SPSS Data Collection Survey Reporter menu Menu Submenu Submenu Keyboard Shortcut File New Alt+F, N Open Ctrl+O Open From IBM Ctrl+D SPSS Data Collection Interviewer Server Administration Save Ctrl+S Save As Alt+F, A xport Tables Alt+F,, T Data Alt+F,, A Print Results Ctrl+P Variables Alt+F, P, V Print Preview Results Alt+F, V, R Variables Alt+F, V, V Advanced Alt+F, C Properties Alt+F, T Recent Files Alt+F, F xit Alt+F, X dit Undo Ctrl+Z Redo Ctrl+Y Cut Ctrl+X Copy Ctrl+C Paste Ctrl+V Delete Delete Select All Ctrl+A Find Ctrl+F View Restore Default Layout Alt+V, R Table List Alt+0 Variable Folders Alt+1 Variable List Alt+2 Design Alt+3 Filter Alt+4 Results Alt+5 Table Notes Alt+6 Table Syntax Alt+7

47 The IBM SPSS Data Collection Survey Reporter User Interface 33 Menu Submenu Submenu Keyboard Shortcut Filter Syntax Alt+8 Variable Preview Alt+9 Toolbars Standard Alt+V, B, S Tables Alt+V, B, T Filter Alt+V, B, F Full Screen F11 Tables New Table Ctrl+T Table For ach Selected Alt+A, N, V Variable Table For ach Selected Alt+A, N, G Grid Summary Means Table Alt+A, N, M Summary Statistic Table Alt+A, N, S Profile Ctrl+R Profile For ach Selected Alt+A, N, R Variable Transpose Table Alt+A, T Summarize By Count Alt+A,B,C Sum Alt+A,B,S Mean Alt+A,B,M New Folder Alt+A, F Generate Selected F5 Table(s) Generate All Tables Ctrl+F5 Global Header and Alt+A, H Footer Sort by Column Alt+A, S Significance Add Difference Alt+A, D Attributes Properties F4 Variables New Ctrl+M New from Side/Top Alt+B, N, S Categorize Alt+B, G Simple Alt+B, G, I Database Alt+B, G, A dit Variable Alt+B, dit Table Variable Alt+B, T Copy Alt+B, C Merge Alt+B, M Hide Alt+B, H Unhide Alt+B, U Show Hidden Variables Alt+B, V Show LevelID Variables Alt+B, L New Folder Alt+B, F

48 34 Chapter 3 Menu Submenu Submenu Keyboard Shortcut Generate Variable Alt+B, P Preview Filter Save Filter As Alt+R, S Move Up Alt+R, U Move Down Alt+R, D Group Alt+R, G Ungroup Alt+R, N xpand Categories Alt+R, Interview Filter Alt+R, I Global Filter Alt+R, F IBM SPSS Data Collection Global Filter Alt+R, use down arrow to select Data Collection Global Filter and press nter Tools View Script for all Tables Alt+O, S View Detailed Statistical Alt+O, D Output Options Alt+O, O Help Topics F1 Getting Started Alt+H, G Variable Type Overview Alt+H, O Accessibility Alt+H, C About IBM SPSS Data Collection Survey Reporter Alt+H, A The dit Variable menu This menu appears in the dit Variable window. Menu Submenu Submenu Keyboard Shortcut File Save Variable Ctrl+S Save Variable As Alt+F, A Clear dits Alt+F, Close Alt+F, C dit Undo Ctrl+Z Redo Ctrl+Y Cut Ctrl+X Copy Ctrl+C Paste Ctrl+V Delete Delete Select All Ctrl+A View View Script Alt+V, S View Properties Alt+V, P Categories Insert Categories Insert Combine Combine Alt+C, C, C

49 The IBM SPSS Data Collection Survey Reporter User Interface 35 Menu Submenu Submenu Keyboard Shortcut Combine and Keep Alt+C, C, K Net Alt+C, C, N Net and Keep Alt+C, C, P Hide Alt+C, H Move Up Alt+Up arrow Move Down Alt+Down arrow Insert Bands Alt+C, B Add Factors Alt+C, F Maximum Number of Alt+C, R Responses Update Counts F9 The IBM SPSS Data Collection Survey Reporter Toolbar Buttons The Standard toolbar Button Action Keyboard Shortcut Create a new table document. Only applies to projects Alt+F, N on the IBM SPSS Data Collection Interviewer Server Administration server. The table document is based on the current Interviewer Server Administration project, and the current user has minimum permissions. Open a survey data file or a table document Ctrl+O (.mtd) file Open a survey data file or a table document Ctrl+D (.mtd) file from the Interviewer Server Administration server Save table document (.mtd) file Ctrl+S Find Cut Copy Paste Delete Undo Redo Help Ctrl+F Ctrl+X Ctrl+C Ctrl+V Delete Ctrl+Z Ctrl+Y F1 The Tables toolbar Button Action Keyboard Shortcut New table Ctrl+T

50 36 Chapter 3 Button Action Keyboard Shortcut dit global filter Alt+R, F Table properties Sort by column significance Set table weight Set table level Transpose table Summarize by count Summarize by sum Summarize by mean Generate results for selected table(s) Generate results for all tables xport results F4 Alt+A, S F4, use right or left arrow key to move to Weight tab F4, use right or left arrow key to move to Level tab Alt+A, T Alt+A,B,C Alt+A,B,S Alt+A,B,M F5 Ctrl+F5 Alt+F,, T For more information, see the topic Creating tables in Chapter 4 on p. 58. The Filter toolbar This toolbar appears in the Filter tab. Button Action Keyboard Shortcut Move the selected filter condition(s) up Alt+R, U Move the selected filter condition(s) down Group the selected filter conditions Ungroup the selected filter conditions xpand categories Alt+R, D Alt+R, G Alt+R, N Alt+R, For more information, see the topic Filtering Your Results in Chapter 6 on p. 92. The Variables toolbar This toolbar appears in the dit Variable window. Button Action Keyboard Shortcut Delete Delete Cut Ctrl+X

51 The IBM SPSS Data Collection Survey Reporter User Interface 37 Button Action Keyboard Shortcut Copy Ctrl+C Paste Undo Redo Update counts Move the selected category up Move the selected category down Combine selected categories Combine selected categories and keep originals Net selected categories Net selected categories and keep originals Ctrl+V Ctrl+Z Ctrl+Y Alt+C, U Alt+Up arrow Alt+Down arrow Alt+C, C, C Alt+C, C, K Alt+C, C, N Alt+C, C, P Insert categories Insert bands Hide category Add Factors Show/hide category properties Show/hide syntax editor Insert Alt+C, B Alt+C, H Alt+C, F Alt+V, P Alt+V, S For more information, see the topic Using variables in Chapter 7 on p Changing the Layout of the IBM SPSS Data Collection Survey Reporter Window You can rearrange the IBM SPSS Data Collection Survey Reporter window in a number of ways to suit the way you work. For example, you can resize individual panes of the window to make the best use of space, and you can move or hide some of the panes in the window if you find you rarely use them. You can also display your results in full-screen mode. By default, the window layout is locked to prevent accidental changes, so before making any changes, you need to unlock it. To unlock the layout From the menu, choose Tools > Options

52 38 Chapter 3 On the Size and Layout tab, check the Allow docking and undocking of window panes check box. You may want to lock the layout again after you have finished changing it. Tomoveapane Place the mouse pointer over the tab that identifies the pane, and click and drag the tab. To hide a pane or toolbar From the menu, choose View or View > Toolbars Deselect the pane or toolbar you want to hide. Alternatively, with the pane at the front of the window, or with the toolbar in a floating location, choose the Close button on the pane. To show a hidden pane or toolbar From the menu, choose View or View > Toolbars You will see a list of the panes or toolbars available. Those that are displayed have a check mark beside them. Select the one you want to display. To resize panes Place the mouse pointer on the dividing line between panes, and click and drag the edge.

53 The IBM SPSS Data Collection Survey Reporter User Interface 39 Figure 3-1 Resizing panes To revert to the default layout From the menu, choose View > Restore Default Layout The default layout is restored. To display results in full-screen mode Choose the Results pane. Press F11. To return to the normal view, press sc. Finding Tables or Variables Use the Find dialog box to find a particular table or variable anywhere in the current table document, by searching for a string of characters in the name or description. You can use the Find dialog box anywhere in the Tables pane or the Variables pane. To use the Find dialog box, choose dit > Find from the menu, or press Ctrl+F, or choose the Find button on the toolbar: Figure 3-2 The Find toolbar button

54 40 Chapter 3 FieldsontheFinddialogbox Find what. nter a string of characters. You can search for: A partial match. Type (or paste in) any words that you want to find. The search finds items that contain any or all of the words. Minor words such as the, a,andand are ignored. For example, asearchforquick brown fox would find items such as brown fox, quick cat, andfoxtrot. An exact match. Type (or paste in) the exact text string surrounded by quotes. The search finds items that contain the exact text typed in (including minor words such as the, a, and and). The text can be part of a longer string. For example, a search for "The quick brown fox" would find The quick brown fox escaped from the cat's grasp, but not A quick brown fox. Match case. By default, the search is not case-sensitive. For example, searching for "quick brown fox", "Quick brown fox", or"quick Brown Fox" all give the same results. To restrict the search to match the case of the search text exactly, check this box. Within. Choose whether to search for the text in the Tables pane or the Variables pane. Look in: You can broaden or narrow your search by choosing either or both of the following options. Name. Search for the string in the table or variable name. Description. Search for the string in the table or variable description. Find Next. Choose this button to move to the next instance of the search string. You can also search for tables or variables directly in the Tables pane or the Variables pane. Undoing and Redoing Actions in IBM SPSS Data Collection Survey Reporter Youcanundoandredoupto50actionsinIBM SPSS DataCollectionSurveyReporter.This includes changes you make in the Table List, the Design pane, the Filter pane, the Table and Filter Syntax panes, and the Table Properties dialog box. You can also undo and redo actions in the dit Variable dialog box using the Undo and Redo options in that dialog box. To undo an action From the menu, choose dit > Undo or press Ctrl+Z, or choose the Undo button on the toolbar: Figure 3-3 Undo button To undo multiple actions, where available, select the drop-down button to the right of the undo button or menu option. A list of previous actions is displayed. Select the earliest action you want to undo. All later actions are also undone.

55 The IBM SPSS Data Collection Survey Reporter User Interface 41 To redo an action From the menu, choose dit > Redo or press Ctrl+Y, or choose the Redo button on the toolbar: Figure 3-4 Redo button To redo multiple actions, where available, select the drop-down button to the right of the undo button or menu option. A list of previous actions is displayed. Select the final action you want to redo. All earlier actions are also redone. The Tables Pane The Tables pane lists all the tables that you create in the table document. Figure 3-5 Selecting a table in the Tables pane The following table explains the icons that appear in the Tables pane. Icon Meaning The table document. This is displayed at the top of the list. If the table document has not been saved, it is shown as Untitled. If it has been saved, the file name is displayed. When you select the table document all generated tables in the document are displayed in the Results pane, with a table of contents listing the tables. Tables that do not contain results. This may either be because no results have been generated for the table or because the table definition has changed since the results were generated (for example, by transposing the table, adding another variable, or changing the cell contents in the table). Tables that contain results. Profile tables that do not contain results. Profile tables that contain results. Invalid tables. A table may be invalid because it was created using a variable that has been deleted, or because it contains a variable that is not valid in the current survey data file. Folders for storing tables. For more information, see the topic Organizing Tables on p. 43.

56 42 Chapter 3 Using the Tables pane, you can: create and delete tables rename tables move tables to a different position in the list organize your tables into folders select one or more tables and carry out other actions on the selected tables (such as editing the properties, generating results, or exporting the results) use standard techniques to resize and move the Tables pane in the IBM SPSS Data Collection Survey Reporter window. Finding Tables You can move directly to a table in the Tables pane by typing the start of the table s name. Tomovetoatable Click anywhere in the list of tables in the Tables pane. Type the first character of the name of the table you want to find. The cursor moves to the next table in the list that begins with the character you typed. If it is not the table that you were searching for, type the same character again to move to the next table in the list that begins with the character. For example, typing r repeatedly would find tables called ranking, rates, rating, etc. Alternatively, type the first two or more characters of the table s name to move to the first table that begins with all the characters typed, for example, typing rat would find rates. Ifyoutype more than one letter of the table s name, you must type the letters quickly or the display will move to a table whose name begins with the second letter. You can also search for text that is part of the table name or description by using the Find dialog box. Renaming Tables You can change the names of your tables, either in the Tables pane or in the Design pane. To rename tables in the Tables pane Right-click the table that you want to rename, and choose Rename from the context menu. Alternatively, highlight the table name and press F2. Type the new name and press nter. To rename tables in the Design pane Select the text in the Table description field, and type the new name.

57 The IBM SPSS Data Collection Survey Reporter User Interface 43 Click away from the fieldtoapplythechange. Organizing Tables You can create folders in the Tables pane to store your tables in, and you can move tables and folders up and down the list. To create folders In the Tables pane, right-click a table name in the location where you want to add the folder. From the context menu, choose New > Folder A new folder with a default name is added to the pane. Right-click the folder name and choose Rename from the context menu, and change it to a suitable name. You can then use the folder to contain tables and other folders. To move tables and folders In the Tables pane, click and drag a table or folder name to move it up or down the list. The cursor changes to a horizontal line: Drop the table or folder when the cursor is at the location where you want to place it. To place a table or folder inside a folder, release the mouse button when the cursor is on top of the folder name. The Variables Folders Pane The Variables Folders pane lists the variables in the survey data file, as well as any new variables that you create. You can select variables from this list to add to the Design pane to create tables, or to the Filter pane to add filters to tables. Figure 3-6 The Variables Folders tab

58 44 Chapter 3 The variables are displayed with icons that indicate their type. For more information, see the topic Variable type overview in Chapter 7 on p In large survey data files there can be hundreds of variables, and even in smaller surveys the variables can have obscure names, which makes finding a particular variable difficult. However, the Variables pane has many features that assist you in finding variables. The Variables pane has two views: the Tree view and the List view. Using either view, you can: create variables or edit existing ones select variables to edit delete variables rename variables select variables to add to the Design pane to create your tables find variables The Tree view Using the Tree view, you can: hide variables that you do not need move variables to a different position in the list organize variables into folders use standard techniques to resize and move the Variables pane in the IBM SPSS Data Collection Survey Reporter window. select one or more variables and carry out other actions on the selected variables (such as deleting, merging, hiding variables in the list, or adding to a table) The List view Using the List view, you can: sort variables To change from the Tree view to the List view From the menu, choose View > Variable List

59 The IBM SPSS Data Collection Survey Reporter User Interface 45 or press Alt+2, or choose the List view tab in the Variables pane: Figure 3-7 Choosing the List view Finding Variables You can move directly to a variable in the Variables pane by typing the start of the variable s name. Tomovetoavariable Click anywhere in the list of variables in the Variables pane. Type the first character of the name of the variable you want to find. The cursor moves to the next variable in the list that begins with the character you typed. If it is not the variable that you were searching for, type the same character again to move to the next variable in the list that begins with the character. For example, typing e in the Variables pane with the Museum sample survey would find entrance, theneducation, thenexpect, etc. Alternatively, type the first two or more characters of the variable s name to move to the first variable that begins with all the characters typed, for example, typing ex would find expect. Ifyou type more than one letter of the variable s name, you must type the letters quickly or the display will move to a variable whose name begins with the second letter. You can also search for text that is part of the variable name or description by using the Find dialog box. Renaming Variables You can change the name of a variable in the Variables pane. The change applies to all tables that use the variable.

60 46 Chapter 3 To rename variables Right-click the variable that you want to rename, and choose Rename from the context menu. Alternatively, highlight the variable name and press F2. Type the new name and press nter. Note: Variable names cannot contain spaces. Organizing Variables You can create folders in the Variables pane to store your variables in, and you can move variables and folders up and down in the list. To create folders In the Variables pane, right-click a variable name in the location where you want to add the folder. From the context menu, choose New > Folder A new folder with a default name is added to the pane. Right-click the folder name and choose Rename from the context menu, and change it to a suitable name. Note: Variable folder names cannot contain spaces. You can then use the folder to contain variables and other folders. To move variables and folders In the Variables pane, click and drag a variable or folder name to move it up or down the list. The cursor changes to a horizontal line: Drop the variable or folder when the cursor is at the location where you want to place it. To place a variable inside a folder, release the mouse button when the cursor is on top of the folder name. Sorting Variables By default, variables are displayed in the Variables pane in the order in which they appear in the survey data file, which is generally the order in which the questions were asked in the survey. You can sort the variables by any of the columns shown in the List view. To sort variables in the Variables pane If the List view of the Variables pane is not already visible, display it by choosing View > Variable List

61 The IBM SPSS Data Collection Survey Reporter User Interface 47 from the menu, or press Alt+2, or choose the List view tab in the Variables pane: Figure 3-8 Choosing the List view Click the heading of the column that you want to use to sort the variables. For example, to sort variables alphabetically by name, click the Name heading. To alternate between ascending and descending order, click the heading again. An arrow in the heading indicates whether the sort is ascending or descending. To revert to the default order, click the box at the top left of the Variables Pane: Figure 3-9 Reverting to default sort order Hiding Variables You can hide individual variables that you do not want to see in the Variables pane.

62 48 Chapter 3 To Hide Variables Right-click a variable name in the Variable List and choose Hide Variables from the context menu. The variable is no longer displayed in the Variables pane (unless you choose to show hidden variables). To Show Hidden Variables From the menu, choose Variables > Show Hidden Variables All hidden variables are shown grayed-out in the Variables pane. To Unhide Variables If necessary, choose the Show Hidden Variables option so that you can see the hidden variables. Right-click a hidden variable name in the Variable List and choose Unhide Variables from the context menu. Printing Variables You can print out a list of all the variables in the Variables pane, including any new variables you have created. The printout prints the name, description and type for each variable. You can also preview the variables before you print them. To display a preview of the variable printout From the menu, choose File > Print Preview > Variables or press Alt+F, V, V. The Print preview dialog box appears. You can use this to check whether the printout is as you require it and to see how many pages it contains. Choose the Print button to open the Print dialog box. To print the variable list Choose the Print button in the Print Preview dialog box, or from the menu, choose File>Print>Variables or press Alt+F, P, V. Select the printer that you want to use. If required, select the pages to print using the Page Range options. Set any printer-specific options as required. Choose Print.

63 The IBM SPSS Data Collection Survey Reporter User Interface 49 The Variable Preview Pane The Variable Preview pane provides you with a summary of the information that is available in a variable, without the need to add it to a table. To display the Variable Preview pane, choose View > Variable Preview from the menu, or press Alt+9. Figure 3-10 TheVariablePreviewpane You can display variable previews for the following types of variable: categorical variables (displayed in a chart or table) numeric variables (displayed in a table) text variables (displayed in a table) categorical grid variables (displayed in a table) You can generate previews for selected variables or for all variables. Displaying Variable Previews The variable preview is displayed on request for variables that you select. Once you have requested a preview for a variable, it is available in subsequent sessions of IBM SPSS Data Collection Survey Reporter. Note that if the data in your survey data file changes, the preview is not updated. To generate a variable preview for selected variables Select a variable in the Variables pane, or use Shift+click or Ctrl+click to select multiple variables.

64 50 Chapter 3 Right-click and choose Generate Variable Preview from the context menu. Select an individual variable to display the preview. To generate a variable preview for all variables From the menu, choose Variables > Generate Variable Preview Choose Generate preview for all variables. Select an individual variable to display the preview. Documentation and Additional Resources IBM SPSS Data Collection Author is supplied with the following documentation: Readme file. Supplied on the CD-ROM and available from the Autoplay menu. Installation Instructions. Supplied on the CD-ROM and available from the Autoplay menu. Online User s Guide (this help file). Installed with Author. Contains full documentation for Author. For more information, see the topic Using the Online Help on p. 50. Data Collection Developer Library. In addition to the Author documentation, advanced users may wish to install the IBM SPSS Data Collection Developer Library. This free resource includes detailed technical documentation on IBM SPSS Data Collection products, the IBM SPSS Data Collection Data Model, and information about creating questionnaires using scripts. The Data Collection Developer Library (sometimes called the DDL) includes sample data and numerous sample scripts. It is available on the Author CD-ROM and as a free download from the Data Collection Developer Library Web site ( Using the Online Help TheOnlinehelpisbasedontheMicrosoftHTMLHelpsystem.ThetopicsareinHTMLand are displayed using the HTML Help viewer, which has many features to help you easily locate information. For more information, see the topic Navigating the Online Help on p. 50. Navigating the Online Help The HTML Help viewer window is divided into two panes. The navigation pane is on the left and the topics are displayed on the right. You can use standard Windows techniques to resize the panes and the viewer window itself. The navigation pane has four tabs: Contents. Displays the table of contents, which organizes the topics logically like the table of contents in a book, with folders corresponding to volumes and chapters. You can use the table of contents to read through the topics sequentially like you would read through a book. When you jump into a topic using the index or search or by following a link, you may sometimes find it useful to look at the next and previous topics in the table of contents. You may find it helpful to spend some time browsing the table of contents, familiarizing yourself with its structure.

65 The IBM SPSS Data Collection Survey Reporter User Interface 51 Note: To open or close all of the folders in the table of contents, right-click the Contents tab and select Open all or Close all. Index. Displays the index, which, like the index in a book, is an alphabetical list of keyword entries. You can scroll through the index or type the first letters of the entry for which you are looking, to jump straight to it. For example, type Print to jump straight to the Print entries. To locate information using the index, either double-click the entry you want or select it and then click the Display button in the lower part of the screen. Some index entries have two levels, but note that using the top-level entry will sometimes lead to topics that are not available through the lower-level entries. Search. Provides a powerful full-text search of all of the information in the online help. You can search for single words, combinations of words, or phrases, and use wildcards and Boolean operators. You can restrict the search to the results of the previous search or to the titles of topics, and choose whether the words for which you are searching are highlighted when you display the topics. For more information, see the topic Searching for Information on p. 51. Favorites. nables you to build a handy list of links to topics that you have found particularly useful. To add a topic to the Favorites tab, you first need to display it using the table of contents, the index, or by following a link to it. Then select the Favorites tab, optionally enter a name for the link, and then click Add. (You may want to give the link a name that helps you remember why you found the topic useful.) After you have added a topic to the Favorites list, you can display it by double-clicking it or selecting it and clicking Display. To remove a topic from the list, select it and click Remove. Note that you will lose your list of favorites when you upgrade to a new version of the online help. Jump to URL. Displays the URL for the current help topic, and enables you to jump directly to another topic by pasting in a URL. This is useful if you have been sent a link to a topic in the form of a URL, or if you want to send a link to a colleague. To display the URL for a topic, right-click on the topic title in the Navigation pane of the Help window, and choose Jump to URL from the context menu. To display a different topic, paste the URL for the topic into the Jump to this URL field, and choose OK. Searching for Information YoucanusetheSearchtabtosearchthrougheverywordintheonlinehelp.Forexample,ifyou search for the word routing, every topic that contains the word routing is listed. Using the search. Select the Search tab and enter the word or phrase you want to find. You can click the Arrow button on the right to enter Boolean operators. Then click List Topics. Todisplay one of the listed topics, either double-click it or select it and click Display. The search is limited to returning the first 500 matching topics. Case sensitivity. The search is not case sensitive. For example, searching for Routing, routing, and ROUTING all give the same results.

66 52 Chapter 3 Words and phrases. If you include more than one word in the search, by default, the words will be combined with the AND operator. This means that the search will return all topics that contain all of the words you have specified regardless of where they appear in the topic. If you want the search to look for the words as a phrase, enclose them in double quotation marks ( ). For example, searching for single response, will return all topics that contain the two words anywhere in the topic, whereas searching for "single response" will return only topics that contain the phrase single response. Punctuation marks. The search ignores punctuation marks. When punctuation marks are embedded in a word, the search considers the two parts of the word to be separate words. This means that when you search for filenames that include the filename extension (such as Museum.mdd), you need to enclose the whole filename in double quotation marks. Highlighting the searched-for words. By default, the search highlights the words you searched for when you view the topics. To switch the highlight feature off, choose Search Highlight Off from the Options menu. (You need to run the search again to make it take effect.) To turn the feature back on, choose Search Highlight On from the Options menu. Sorting the results. The Search tab lists the topics found using three columns Title, Location, and Rank. By default, the topics arelistedinrankorder,butyou can click the headings of the columns to change the sort order. For example, if you want to sort the topics by the topic title, click the Title column heading. Matching similar words. When this feature is selected, the search selects the grammatical variations of a word or phrase. For example, if you search for the word question, the search returns topics containing the words questions and questionnaire as well as topics containing the word question. You turn this feature on and off by selecting or deselecting Match similar words in the lower part of the window. This feature is on by default. Searching the results of a previous search. If the search returns a large number of topics, you may want to refine the results by restricting a new search to the results of the previous search. You do this by selecting Search previous results in the lower part of the window. Searching topic titles only. Select Search titles only in the lower part of the window to restrict the search to the topic headings rather than the entire contents of each topic in the online help. Operators. You can combine words using the AND, OR, NOT, and NAR operators, as shown in the following table. Use the arrow button to the right of the search text box to insert operators into the search query. Alternatively, you can type the operators into the search text box. Operator AND OR NOT NAR Searches for Both words in the same topic. ither or both of the words in the same topic. Topics containing the first word but not the second word Topics containing both words, close together (within about eight words).

67 The IBM SPSS Data Collection Survey Reporter User Interface 53 Wildcards. You can use the asterisk character (*) and the question mark character (?) as wildcards in words. However, they do not work as wildcards when you use them in a phrase contained in double quotation marks. Wildcard Description * Represents any number of characters in a word or no characters. For example, *group, returns topics containing the word group and topics containing ungroup.? Represents a single character in a word. For example, m?d returns topics containing mqd and mdd but not mqqd or md. xamples. The following table provides some examples of using the search syntax. Search For Single AND response Single response Single OR response response NOT single single NAR response Single response *group?ar Results All topics that contain both words. The same as Single AND response. All topics that contain either or both words. All topics that contain response but not single. All topics that contain the two words close to each other within the text (within about eight words). All topics that contain the phrase Single response. All topics that contain the word group and all topics that contain the word group with a prefix of one or more characters. This search would be useful if you want to return topics containing the word ungroup as well as the word group. All topics that contain the word ar when it is prefixed by one character only. This search would therefore return topics containing the word bar and car but not the word star. Printing Information To print one topic Select the topic in the table of contents. Click the Options tool or right-click the topic, and then select Print.

68 54 Chapter 3 Figure 3-11 The Print menu option Select Print the selected topic andthenclickok. To print all of the topics in a folder Select the folder in the table of contents. Click the Options tool or right-click the topic, and then select Print. Figure 3-12 The Print menu option Select Print the selected heading and all subtopics andthenclickok. Warning: Be careful not to print a folder that contains many subfolders because this may require a large amount of system memory and many sheets of paper. Using the Toolbar Tool Description Keyboard Shortcuts Hides the navigation pane (when Alt+O, T it is visible). Shows the navigation pane (when it is hidden). Alt+O, T

69 The IBM SPSS Data Collection Survey Reporter User Interface 55 Tool Description Keyboard Shortcuts Displays the last topic you viewed. Returns to the topic you were viewing before you used the Back tool. This tool is available only when you have used the Back tool. Stops the loading of an HTML page. This is useful when you are viewing pages on the World Wide Web. Reloads the current HTML page. This is useful when you are viewing pages on the World Wide Web. Cycles between five different font sizes. Alt+O, B Or Alt+Left arrow Alt+O, F Or Alt+Right arrow Alt+O, S Or sc Alt+O, R Or F5 The Options menu. This contains commands corresponding to the tools on the toolbar and the additional commands listed below. Alt+O Options Menu Command Description Keyboard Shortcuts Hide Tabs Hides the navigation pane (when Alt+O, T it is visible). Show Tabs Shows the navigation pane (when Alt+O, T it is hidden). Back Displays the last topic you viewed. Alt+O, B Or Alt+Left arrow Forward Returns to the topic you were viewing before you used the Back tool. This tool is available only when you have used the Back tool. Alt+O, F Or Alt+Right arrow Home Returns you to the Welcome topic. Alt+O, H Stop Stops the loading of an HTML page. This is useful when you are viewing pages on the World Wide Web. Alt+O, S Or sc Refresh Internet Options Reloads the current HTML page. This is useful when you are viewing pages on the World Wide Web. Opens the standard Internet xplorer Internet Options dialog box. Alt+O, R Or F5 Alt+O, I

70 56 Chapter 3 Command Description Keyboard Shortcuts Print Displays the Print Topics dialog Alt+O, P box, which gives you the option to print a selected topic or a selected section of topics. Search Highlights Off Turns off the feature that Alt+O, O highlights the words for which you are searching. Search Highlights On Turns on the feature that highlights the words for which you are searching. Alt+O, O Navigating Using the Keyboard General Navigation To: Switch between Navigation and Contents panes Scroll downwards through a topic Scroll upwards through a topic Scroll through all of the links in a topic or all of the options on a tab in the navigation pane Press: F6 and Page Down and Page Up Tab Contents tab To: Select the Contents tab Open a folder Close a folder Select a topic or folder Display the selected topic Scroll the Contents pane to the left Scroll the Contents pane to the right Scroll the Contents pane up Scroll the Contents pane down Press: Alt+C or nter Ctrl+ Ctrl+ Ctrl+ Ctrl+ Index tab To: Select the Index tab Select an entry in the list Display the selected topic Press: Alt+N or nter Search tab To: Select the Search tab Press: Alt+S

71 The IBM SPSS Data Collection Survey Reporter User Interface 57 To: Type a word to search for To begin the search Select a topic in the results list Select or deselect Search previous results Select or deselect Match similar words Select or deselect Search titles only Press: Alt+W, and then type the words Alt+L or nter Alt+T and then and Alt+U Alt+M Alt+R Favorites tab To: Select the Favorites tab Add the current topic to the Topics list Select a topic in the Topics list Display the selected topic Removed the selected topic from the Topics list Change the name for the current topic Press: Alt+I Alt+A Alt+P and then and Alt+D Alt+R Alt+U and then type the new name For keyboard shortcuts for the tools on the toolbar and the commands on the Options menu, see Using the Toolbar.

72 Creating tables Chapter 4 Using IBM SPSS Data Collection Survey Reporter, you can create multiple tables to analyze your data and generate results for different combinations of variables. How table sequence affects population time The table sequence directly affects the table population time. To understand this, we must first understand aggregation. When aggregating data, TOM scans data from beginning to end. The scanning is based on the HDATA structure. When variables on several tables are at the same level structure, and share the same bottom level, data aggregation is accomplished in a single pass. What is the same level structure? Using household.mdd as an example, person[..].trip[..].country and person[..].gender are at the same level structure because the trip level is the child of the person level. All of the variables under the two levels are at the same level structure. All variables at the top level are considered to be at the same level structure as the other levels. Although person[..].trip[..].country and person[..].gender are at the same level structure, their level is actually different. The level for person[..].trip[..].country is person[..].trip while the level for person[..].gender is person. What is bottom level? A table contains several variables on the side and top. ach variable has its own level, and the lowest level is regarded as the bottom level. For example, the bottom level for the following table is person[..].trip. Person[..].trip[..].gender>region*person[..].occupation Variable Person[..].trip[..].gender Region Person[..].occupation Level person[..].trip HDATA person The lowest level among HDATA, person, person[..].trip is person[..].trip. How should tables be organized? Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

73 59 Creating tables If tables that have the same bottom level are grouped together, you can aggregate the table values in a single pass. For example, the following sequence of tables requires four passes in order to aggregate data: Table1 Table2 Table3 Table4 region*housetype region*person[..].occupation region* tenure region*person[..].gender Now examine the following sequence of tables that only requires two passes: Table1 Table2 Table3 Table4 region*housetype region* tenure region*person[..].occupation region*person[..].gender Assuming that each pass takes one minute to complete, the first table sequence will take four minutes to populate while the second will take two minutes to populate. Creating a table You create tables by selecting variables on the Variables pane and adding them to the Design pane, then generating the results for the table. Creating a table From the menu, choose: Tables > New > Table or press Ctrl+T, or choose the Create Table button: Figure 4-1 Create table button In the Design pane, enter a description for the table. In the Variables pane, select a variable (or use Shift+click or Ctrl+click to select multiple variables). Drag the cursor to the Add button to add the variable(s) to the side of the table or the top of the table as required. If you have selected multiple variables, they are added in the order in which you selected them. Tip: You can add all the variables in a folder to a table by dragging and dropping the folder instead of selecting all the variables. Choose the Results pane or press F5 to generate the table and display the results.

74 60 Chapter 4 Creating multiple tables with the same top variable You may want to create several tables using the same variable or variables on the top of the table. For example, demographic variables are often combined to form a banner or breakdown, which is then used to crosstabulate a number of different variables. This topic explains how to create multiple tables, each one of which crosstabulates one variable against the same banner variable(s). Create multiple tables with the same top variable From the menu, choose: Tables > New > Table In the Variables pane, use click, Shift+click or Ctrl+click to select the variables to add to the top of the table. Click and drag to add the variable(s) to the top of the table in the Design pane. In the Variables pane, use Shift+click or Ctrl+click to select the variables to use as the side variables. From the menu, choose: Tables > New > Table For ach Selected Variable A separate table is created for each side variable. All the tables have the same variables that you added to the top of the first table. From the menu, choose: Tables > Generate All Tables or press Ctrl+F5, or choose the Generate All toolbar button: Figure 4-2 Generate all tables button Switching the top and side variables in a table You can switch the orientation of the table after you have created it, so that the variables on the side move to the top and vice versa. Switchingthe top and side variables on a table In the Tables pane, select the table you want to change. Choose the Transpose Table button: Figure 4-3 Transpose table button The variables on the side and top of the table change places.

75 61 Creating tables Note: If the table previously contained results, transposing the table removes the results. Generate the table: Figure 4-4 Generate table button Adding and nesting variables When you add a second or subsequent variable to the side or top of a table, you can either add the variables or nest them. Adding variables In the Variables pane, highlight a variable. Click and drag the variable to the Add button in the Design pane. Adding variables simply displays one variable after another on the table, as though they are separate tables in the same display. For example, here is a table in which two variables (gender and interview) areaddedtothetopofatable: Figure 4-5 Tablewithtwovariablesaddedtothetopaxis Nesting variables In the Variables pane, highlight a variable. Click and drag the variable to the Nest button in the Design pane.

76 62 Chapter 4 Nesting variables provides a breakdown of detail. When you nest variables, the categories of the inner variable are displayed for each category of the outer variable. Here is a table that has the same two variables on the top as in the previous table, but this time gender is nested within the interview variable: Figure 4-6 Table with two variables nested on the top of the table Whether you choose to add variables or nest them depends on what kind of analysis you want. The first table shows the number of male and female respondents and their age breakdown and the number of people interviewed entering and leaving the museum and their age breakdown. However, it does not show the gender breakdown of the respondents interviewed entering and leavingthemuseum.forthatyouneedtonestthegender variable within the interview variable (which records whether respondents were interviewed entering or leaving the museum) as shown in the second table.

77 63 Creating tables Creating tables using grid variables Surveys frequently include grid questions. These typically ask respondents to choose a rating on apredefined scale for a number of products in a list. For example, the Museum sample survey contains the following grid question (which is called rating): Figure 4-7 Rating grid It is generally easier to analyze data collected using a grid question as a grid table. Creating a table using a grid variable From the menu, choose: Tables > New > Table In the Variables pane, select the grid variable you want to use: Figure 4-8 Selecting a grid variable

78 64 Chapter 4 ClickanddragthevariabletotheAddGridbuttonontheDesignpane: Figure 4-9 Adding a grid variable The grid is addedtothetable. Generate the table: Figure 4-10 Generate table button Here is the table for the Rating grid question: Figure 4-11 Grid table

79 65 Creating tables By default, the orientation of the grid table is taken from the definition of the grid question in the metadata. However, you can override the default orientation if required by choosing the Transpose Table button: Figure 4-12 Transpose table button Creating multiple grid tables You can create multiple grid tables at the same time. Use Shift+click or Ctrl+click in the Variables pane to select the grid variables. From the menu, choose Tables > New > Table For ach Selected Variable or simply drag all the selected grid variables to the Add Grid/Loop button. Creating Summary Statistic or Summary Means tables You may find it useful to summarize a number of different numeric variables in a single table. You can create a summary table by selecting the numeric variables that you want to summarize and then using the Summary Statistics Table dialog box to select the statistics that you want to see. For example, the following table summarizes five questions (visits, visits12, adults, under16s,and under11s) that were asked in the original Museum survey, dealing with respondents previous visits and the numbers of people of different ages in their group during the current visit. It shows the mean values for each of these questions, tabulated by age of respondent. Figure 4-13 Table with mean scores for various variables on the side and Age on the top This example shows a summary table that provides the mean value for each variable by using a mean cell item. You can produce other types of summary statistic tables for any cell item that can be based on a numeric variable, for example, maximum, minimum, or standard deviation. For a full list, see the Summary Statistic Table dialog box.

80 66 Chapter 4 Creating a Summary Statistic table In the Variables pane, select the variables that you want to summarize: Figure 4-14 Selecting variables to add to a summary table From the menu, choose Tables > New > Summary Statistic Table In the Summary Statistic Table dialog box, select the statistic(s) that you want to see for each variable. The default values are sum, minimum, maximum, and mean. The Summary Statistic Tables feature can only be applied on numeric variables. If you select a categorical variable, a error message will display. When creating the summary statistic table, you can also choose whether to summarize all the variables in a single new variable, instead of displaying each variable separately on the side of the table. Check the Display as single axis box. Choose OK to close the dialog box. A new table is created and the variables are added to the side of the table. If you selected Display as single axis, a single variable is created and added to the table, containing a row for each selected variable. If you want to add any variables to the top of the table, select and add the variables using drag anddroporctrl+alt+t. Generate the table: Figure 4-15 Generate table button Displaying the summarized variables as a single variable If you select the Display as single axis option, IBM SPSS Data Collection Survey Reporter creates a new variable called SummaryVariable and adds it to the side of the table. SummaryVariable contains a single row for each of the selected variables. The cell items correspond to the summary statistics that you selected.

81 67 Creating tables If you include the base as one of the summary statistics, the base in all the rows is for all cases: Figure 4-16 Table with mean scores for various variables on the side and Age on the top Displaying the summarized variables as separate variables IfyoudonotusetheDisplayassingleaxisoption, Survey Reporter adds the selected variables to the side of the table and edits them so that they each display a single row. The cell items in the row correspond to the statistics that you selected. If you include the base as one of the summary statistics, the base in each row is the (non-null) cases for the variable in that row: Figure 4-17 Table with the same selection of variables, but with Display as single axis deselected Summary Statistic Table dialog box The Summary Statistic Table dialog box provides a quick way of creating tables of means or other statistics for a number of numeric variables.

82 68 Chapter 4 Figure 4-18 The Summary Statistic Table dialog box To use the Summary Statistic Table dialog box, select the variables that you want to summarize in the Variables tab, then choose Tables > New > Summary Statistic Table from the menu, or press Alt+A, N, S. Fields in the Summary Statistic Table dialog box Select summary statistics to display for each variable. These are the cell items that will be displayed for each variable. The default is the mean. Choose from any of the following cell items: base. The total number of cases that are eligible for inclusion in a variable, a row, a column, or a table. The base is used in statistical tests and for calculating percentages. Note that the base is that for the variable or variables displayed on the side of the table. If you select the Displayassingleaxisoption, the base in each row is the base for all cases. If you deselect this option, each variable is added separately to the side of the table, and the base in each row is for the variable summarized in that row. sum. The sum or total of the values. minimum. The smallest value. maximum. The largest value. mean. A measure of central tendency. It is the arithmetic average; the sum divided by the number of cases. range. The difference between the largest and smallest values the maximum minus the minimum. mode. The most frequently occurring value. If several values share the greatest frequency of occurrence, each of them is a mode. median. The value above and below which half the cases fall; the 50th percentile. If there is an even number of cases, the median is the average of the two middle cases when they are sorted in ascending or descending order. The median is a measure of central tendency not

83 69 Creating tables sensitive to outlying values unlike the mean, which can be affected by one or more extremely high or low values. standard deviation. A measure of dispersion around the mean. In a normal distribution, 68% of cases fall within one standard deviation of the mean and 95% of cases fall within two standard deviations. For example, if the mean age is 45 with a standard deviation of 10, then 95% of the cases would be between 25 and 65 in a normal distribution. standard error. A measure of how much the value of the mean may vary from sample to sample taken from the same distribution. The standard error of the sample mean can be used to estimate a mean value for the population as a whole. In a normal distribution, 95% of the values of the mean should lie in the range of plus and minus two times the standard error from the mean. Additionally, the standard error can be used to roughly compare the observed mean to a hypothesized value of another mean (that is, you can conclude the two values are different if the ratio of the difference to the standard error is less than -2 or greater than +2). sample variance. This is the sample variance, which is a measure of dispersion around the mean, equal to the sum of squared deviations from the mean divided by one less than the number of cases. The sample variance is measured in units that are the square of those of the variable itself. Display as single axis? If you check this box, a new variable is created and added to the side of the table, containing a row for each selected variable. This option is available only for numeric variables. If you deselect this box, each variable is added separately to the side of the table. Creating Summary Means tables The column means test can only be run against the mean element. It will not work for the mean cell items in the summary statistic table. To run column means test against a range of variables, which can include both numeric and categorical variables, you need to use the Summary Means Table. The following shows a sample summary statistics table (based on visits, visits12, adults,andage). Figure 4-19 Table with sample summary statistics You can see that the column means test is applied. This example displays a summary means table that provides the mean value for each variable by running the column means test using a mean element.

84 70 Chapter 4 Creating a Summary Means table In the Variables pane, select the variables that you want to summarize and select Tables > New > Summary Means Table from the menu, or press Alt+A, N, M. The Summary Means Table dialog displays, allowing you to choose if the column means test is applied to the table and, if all selected variables are numeric, if they can be displayed in a single axis variable. Figure 4-20 Summary Means Table dialog Select the appropriate options and click OK to close the dialog. A new table is created and the variables are added to the side of the table. If you selected Displayasasingleaxis,asingle variable, that contains a row for each selected variable, is created and added to the table. If you want to add any variables to the top of the table, select and add the variables using drag anddroporctrl+alt+t. Displaying the summarized variables as a single variable If all of the variables are numeric, you can choose to display them within a single variable by selecting the Display as a single axis option. IBM SPSS Data Collection Survey Reporter creates a new variable called SummaryVariable and adds it to the side of the table. SummaryVariable contains a single mean element row for each of the selected variables. Figure 4-21 Table with summarized variables as a single variable

85 71 Creating tables Displaying the summarized variables as separate variables If you do not use the Displayasasingleaxis option, Survey Reporter adds the selected variables to the side of the table and edits them so that they each display a single row. Figure 4-22 Table with summarized variables as separate variables Detection of the existing mean element If the variable contains a mean element in its axis expression, Survey Reporter will automatically use the setting of that mean element. However, in the Displayasasingleaxisscenario, the label will be overridden with the variable label. Copying a table You can copy a table and use it as the basis for a new table. This copies all the information that you have set up for the table, including the table structure, table description, table properties, and table filter. Note: To copy just the table structure (the syntax for the variables making up the side and top of the table) see Copying table syntax. Copying a table Select the table in the Tables pane. Figure 4-23 Selecting a table

86 72 Chapter 4 From the menu, choose dit > Copy or press Ctrl+C, or choose the Copy button on the toolbar: Figure 4-24 Copy button From the menu, choose dit > Paste or press Ctrl+V, or choose the Paste button on the toolbar: Figure 4-25 Paste button A new table is placed at the end of the list of tables. You can move this to another location if required. For more information, see the topic Organizing Tables in Chapter 3 on p. 43. Viewing and copying the table script The View script for all tables dialog allows you to copy the script for all tables to use as the basis for new tables. You can highlight and copy specific script sections, copy all script, or save all ofthescripttoan.mrs file. Include edited variables. When checked, the generated script contains all edited variable information. When unchecked, the generated script does not contain any edited variable information. Copy All. This copies all the information that you have set up for the table, including the table structure, table description, table properties, and table filter, to the clipboard. You can paste the information into the application of your choosing. Save As... Displays the Save As dialog, allowing you to save all of the table script information to an.mrs file. Deleting a table You can delete part or all of the structure of a table(thevariablesmakingupthesideandtopofthe table) without deleting other information that you may have set up for the table, such as the table description, table properties, or filters.youdothisonthedesignpane. Alternatively, you can delete an entire table, including all the information associated with it, by selecting the table on the Tables pane.

87 73 Creating tables Deleting the structure of a table Select the table, or the area of the table, on the Design pane. To delete a variable, click the variable name to select it: Figure 4-26 Selecting a variable on a table To delete a number of variables, use Ctrl+click to select them: Figure 4-27 Selecting multiple variables on a table

88 74 Chapter 4 To delete all the variables on the top or side of a table, click inside the Top or Side area: Figure 4-28 Selecting the top of a table To delete the whole table structure, click outside the Top or Side area: Figure 4-29 Selecting the table structure

89 75 Creating tables Press the Delete key or choose the Delete button on the toolbar: Figure 4-30 Delete button This deletes the selected part of the table structure, but retains the table description as well as any filters or table properties you have set up. Deleting an entire table Select the table that you want to delete in the Tables pane: Figure 4-31 Selecting the entire table Press the Delete key or choose the Delete button on the toolbar: Figure 4-32 Delete button This deletes the table, including any filters or table properties that you have set up. Bulk updating table definitions Starting with version 6.0.1, IBM SPSS Data Collection Survey Reporter allows you to bulk update the banners (top axis) and side axis for multiple tables. When you select multiple tables, that have same side or top axis, the side and top axis will display as a single table. Changes appliedtoside or top axis design controls will apply for all selected tables. When the selected, multiple tables have different side or top axes, the Multiple specifications place holder will display on the side or top axis design control.

90 76 Chapter 4 Figure 4-33 Multiple table definition bulk update The Multiple specifications place holder indicates that the selected tables have different side or top axes. The place holder can only be replaced or deleted. Replacing the Multiple specifications place holder You can replace the place holder by selecting different variables and clicking Replace on the side or top design control. After clicking Replace, the side or top axes for all selected tables are replaced with the selected variables. Deleting the Multiple specifications place holder You can delete the Multiple specifications place holder by selecting the place holder and pressing the Delete key. After pressing Delete, the side and top axes are cleared for all selected tables. Profile tables and difference attribute tables The bulk update process is skipped for profile tables and difference attribute tables. Bulk updates continue for other tables. Advanced multiple table definitions The Design Tab displays multiple tables in a graphical format. The full table definition displays in the Table Syntax pane at the bottom of the screen. The place holder is identified in the table definition as %Multiple specifications%. Using the tables displayed in the image above as an example, selecting two tables that have same top axis but different side axis will display the following in the Table Syntax pane: %Multiple specifications% * age > gender

91 77 Creating tables The %Multiple specifications% place holder can only be removed or replaced in the Table Syntax pane. Click Apply to validate the current syntax. If the syntax is valid, the Design pane will automatically update to display the table structure. If the syntax is not valid, an error will display. Click Cancel to return the previously applied syntax. Advanced table definitions This section contains information on creating advanced table definitions, including: diting a table definition using the Table Syntax pane Copying table syntax xample: Creating table definitions using non-categorical variables diting a table definition using the Table Syntax pane In the Design tab, the table definition appears in graphical format. You may have noticed that as you create a table in this tab, the full table definition is displayed in the Table Syntax pane at the bottom of the screen. For example, if you create the tables described in Adding and nesting variables, the Table Syntax pane displays: age * gender + interview for the first table, and: age * interview > gender for the second table. This is useful, for example, when you want to copy and paste the table definition into another table, or into a script in another application. You can also edit the table definition directly in this pane once you become familiar with the syntax, and you can even use this pane to create a table definition from scratch. Displaying the Table Syntax pane if it is not visible From the menu, choose View > Table Syntax The pane appears at the bottom of the screen. You can resize it and move it around the IBM SPSS Data Collection Survey Reporter window as required. diting the table syntax Place the cursor in the Table Syntax pane and type in the table definition.

92 78 Chapter 4 To validate and apply the syntax, choose the Apply button. If the syntax is valid, the Design pane is automatically updated to show the table structure. If it is not valid, an error is displayed. If you make a mistake while editing the syntax, choose the Cancel button to return to the previously applied syntax. For more information, see the topic Table Specification Syntax in Chapter 19 on p You can use any expression that is supported by the IBM SPSS Data Collection Data Model, including the functions in the IBM SPSS Data Collection Function Library. See the Function List for details of the functions available. See also the xpression valuation and Data Collection Function Library topics in the IBM SPSS Data Collection Scripting section of the IBM SPSS Data Collection Developer Library for further information on syntax. Copying table syntax You can copy the structure of a table (the syntax for the variables on the side and top of the table) and paste it into another table, using the Table Syntax pane. Note: Using this method copies only the structure of the table. To copy the entire table, including the description and any table properties or filters, see Copying a table. Copying the table syntax If the Table Syntax pane is not visible, choose View > Table Syntax from the menu, or press Alt+7. In the Tables pane, select the table you want to copy from. Figure 4-34 Selecting a table From the menu, choose dit > Copy or press Ctrl+C, or choose the Copy button on the toolbar: Figure 4-35 Copy button Select the table you want to copy to, or press Ctrl+T to create a new table. Place the cursor in the Table Syntax pane and press Ctrl+V.

93 79 Creating tables Choose the Apply button. xample: Creating table definitions using non-categorical variables When you create a table using a variable other than a categorical variable (for example, a numeric or text variable) you need to create an axis expression for the variable. In the case of numeric variables, IBM SPSS Data Collection Survey Reporter automatically adds a default axis expression for any numeric variable that you add to a table using the Design pane. However, as the Table Syntax pane is an advanced feature, Survey Reporter makes no assumptions about what you want to include in the table definition, so you must enter a valid axis expression for the numeric variable. For example, you can create a table in the Design pane by dragging and dropping the visits variable onto the side of the table and the gender variable onto the top. This results in the following table: Figure 4-36 Table of visits by gender with default axis expression However, if you try to create this table using the Table Syntax pane by typing: visits * gender an error is displayed when you choose the Apply button. This is because the visits variable is a numeric variable and so requires an axis expression. If you create the above table using the Design pane and look at what is displayed in the Table Syntax pane, you will see that it shows the following syntax: visits{base(), 'Mean' mean(visits), 'Min' min(visits), 'Max' max(visits), 'stddev' stddev(visits)} * gender The highlighted section is the default axis expression for the numeric variable, which Survey Reporter has added automatically. To create a table containing the visits variable using the Table Syntax pane, you would need to add this axis expression, or create another axis expression containing the information you want to see. For details of how to create valid axis expressions for different types of variable, see the Table Specification Syntax section.

94 Changing Cell Contents Chapter 5 When you build a table, generally the main information that you are trying to convey is the figures in the cells. The figures in the cells are called the cell contents. The following table provides a summary of the different types of cell contents. For a full list of the types of cell contents available, see Table Properties: Cell Contents. Type Counts Unweighted counts Percentages Indices Summary statistics of a numeric variable xpected values Residuals Description These show the number of cases that satisfy the row and column conditions for each cell. If the table is weighted, the counts are the weighted counts. In a weighted table, these are the unweighted counts. In an unweighted table, the counts and the unweighted counts are identical. These express the count or sum of a numeric variable as a percentage of the base for the column, row, or table. xpressing figures as percentages can make it easier to interpret and compare the data in a table. You can optionally choose to express row and column percentages as cumulative percentages. These are calculated for each cell by dividing the row percentage in the cell by the row percentage for the same column in the base row. Indices show how closely row percentages in a row reflect the row percentages in the base row. The nearer a row s indices are to 100%, the more closely that row mirrors the base row. You can show a summary statistic of a numeric variable for the cases in each cell. For example, in a table of age by gender, you can use the visits numeric variable to show the sum of the number of previous visits made to the museum by the respondents in each cell. Alternatively you can show the mean number of previous visits made by the respondents in each cell. Other options include the minimum value, maximum value, range, mode, median, percentile, standard deviation, standard error, and variance. These show the count or sum of a numeric variable that would be expected in the cell if the row and column variables are statistically independent or unrelated to each other. These show the difference between the count or sum of a numeric variable and the expected values. Large absolute values for the residuals indicate that the observed values are very different from the predicted values. You can specify the number of decimal places with which you want the cell contents to be shown. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

95 81 Changing Cell Contents Adding and Removing Cell Contents By default, the contents displayed in each cell of a table are counts and column percentages. You can change the cell contents to add or remove items as required. To add or remove cell contents In the Tables pane, select the table that you want to edit. From the menu, choose Tables > Properties Choose the Cell Contents tab. Select an item in the Available items list and choose the >> button to add it to the table. For cell contents that are based on a variable, for example Minimum or Maximum, you must also specify the variable to use. Highlight the item in the Included in cells list and select a variable from the Based on list. You can also add a prefix orsuffix, or change the number of decimal places shown in the cell for the item, using the options in the Details section. To remove an item, select it in the Included in cells list and choose the << button. Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. Counts and Unweighted Counts Counts show the number of cases that satisfy the row and column conditions for each cell after any weighting defined for the table has been applied. Counts are the basic values that are shown in the cells of a table. Unweighted counts show the number of cases that satisfy the row and column conditions for each cell before any weighting defined for the table has been applied. In an unweighted table, the counts and unweighted counts are identical. The following table shows both weighted and unweighted counts in all of the cells apart from those formed from the unweighted bases. By default, an unweighted base is added to all weighted tables. For more information, see the topic Showing the Unweighted Base in Weighted Tables in Chapter 10 on p. 261.

96 82 Chapter 5 Figure 5-1 Table showing counts and unweighted counts In this table, the first figure in the cells is the count (which is weighted) and the second is the unweighted count. The table is weighted using the genbalance weighting variable, which uses non-integer sample weights to weight the sample to an equal balance between the two genders. More males than females were interviewedinthesurvey,sothegenbalance weighting variable inflates the responses from female respondents and deflates the responses from male respondents. If you look at the unweighted counts in the njoyment row, you can see that of the people who selected this category, 14 have a biology qualification and 31 don t. The unweighted counts are always whole numbers because a respondent either does or does not select each category. If you look at the weighted counts in the same row, you can see that the figures are and 31.12, respectively. The weighted counts are non-integers because they represent the unweighted counts multiplied by the appropriate weights, which in this example are non-integer values. For more information, see the topic Applying Weighting in Chapter 10 on p In practice, counts are generally shown as whole numbers. You can specify this by setting the number of decimal places to zero. For more information, see the topic Adding and Removing Cell Contents on p. 81.

97 83 Changing Cell Contents Percentages Percentages express the count or sum of a numeric variable as a percentage of the base for the column, row, or table. xpressing figures as percentages can make it easier to interpret and compare the data in a table. The following table shows both counts and column percentages. Figure 5-2 Table showing counts and column percentages In this table, the first figure in each cell is the count and the second is the column percentage. The count in the Base column of the Base row shows that 304 respondents were asked both of the questions that the variables in the table are based on. These respondents form the sample base for the table. The counts in the first row after the Base row show that 118 people described their expectation as General knowledge and education, and of these people, 25 hold a biology qualification and 93 do not. The column percentages show that 39% of the respondents in the table describe their expectation as General knowledge and education. A higher percentage of those who do not have a biology qualification (41%) expected to gain general knowledge than those with such a qualification (32%). Sometimes, rounding means that the percentages for single response variables do not always add up to 100%. If you add up all of the percentages in the No column in the above table, you will see that they add up to 101% rather than 100%. This is because IBM SPSS Data Collection Survey Reporter performs all calculations using the maximum possible accuracy and only performs rounding immediately before it displays figures in a table. For more information, see the topic Rounding in IBM SPSS Data Collection Survey Reporter in Chapter 19 on p You can use the Adjust rounding so that percentages add up to 100% option in the Display tab of the Table Properties dialog box to force the percentages to add up to 100%.

98 84 Chapter 5 Here is the table after the rounding has been adjusted. Notice that the percentages in the No column now add up to 100%: Figure 5-3 Table showing counts and column percentages with rounding adjusted to add up to 100% Note that the biology and expect variables are both single response variables. In multiple response variables, percentages do not usually add up to 100% and adjusting the figurestodosowould not make sense. In the next table, the column percentages are shown as cumulative percentages.

99 85 Changing Cell Contents Figure 5-4 Table showing counts and cumulative column percentages In this table, the column percentages are shown with two decimal places. In all other respects the column percentages in the first row after the Base rowarethesameasthoseshowninthecolumn percentages table shown earlier. However, the percentages in the subsequent rows differ. This is because the column percentages for each successive row are added to those of the previous rows to make a cumulative percentage, so the cumulative percentage for the final row is 100%. Notice that in this table the column percentages are not shown in the Base row. This has been achieved by deselecting the Show 100% in base rows/columns optioninthedisplaytab of the Table Properties dialog box. The next table shows counts, and row and total percentages.

100 86 Chapter 5 Figure 5-5 Table showing counts and row and total percentages In this table the first figure in each cell is the count, the second is the row percentage, and the third is the total percentage. Row percentages show us what percentage of the respondents in each row fall in each column. For example, if you look at the General knowledge and education row, you can see that 21% of the respondents in the row hold a biology qualification, whereas 79% of them do not. Similarly, total percentages show us what percentage of the total number of respondents in the table fall in each cell of the table. Looking at the General knowledge and education row again, you can see that respondents in the row who hold a biology qualification make up 8% of the respondents in the table and those in the same row without a biology qualification make up 31% of the total for the table. Note: If you have a table that contains only percentage values, you may want to display the table without any percent signs. You can do this using the Display percent signs option in the Display tab of the Table Properties dialog box.

101 87 Changing Cell Contents Indices Indices are calculated for each cell by dividing the row percentage in the cell by the row percentage for the same column in the base row. Indices show how closely row percentages in a row reflect the row percentages in the base row. The nearer a row s indices are to 100%, the more closely that row mirrors the base row. The following table shows row percentages and indices. Figure 5-6 Table showing row percentages and indices Looking at the table, we can see that the indices in the Other row are closest to 100%. Let s look at the No column. The index of 99 was created by dividing the row percentage of 74% by 75%, the row percentage for the No cell in the Base row. If we look at the row percentages in the Other row, we can see that at 26% and 74% they closely match the row percentages of 25% and 75% in the Base row. Summary Statistics of Numeric Variables You can show summary statistics of numeric variables for the cases in the cells of a table. For example, if you create a table of age by gender using the Museum data set, you can show the total number of previous visits made to the museum by the respondents in each cell by using the Sum cell contents option and the visits variable. Similarly, you can use the Mean cell contents option to show the average number of previous visits made by the respondents in each cell. In weighted tables, all of the summary statistics apart from the minimum and maximum values are always weighted. If you want to show unweighted summary statistics, you must remove the weighting from the table.

102 88 Chapter 5 You can use the following summary statistics for cell contents: Mean. A measure of central tendency. It is the arithmetic average; the sum divided by the number of cases. Sum. The sum or total of the values. Minimum. The smallest value. Maximum. The largest value. Range. The difference between the largest and smallest values the maximum minus the minimum. Mode. The most frequently occurring value. If several values share the greatest frequency of occurrence, each of them is a mode. Median. The value above and below which half the cases fall; the 50th percentile. If there is an even number of cases, the median is the average of the two middle cases when they are sorted in ascending or descending order. The median is a measure of central tendency not sensitive to outlying values unlike the mean, which can be affected by one or more extremely high or low values. Percentile. A value that divides cases according to values below which certain percentages fall. For example, the 25th percentile is the value below which 25% of cases fall. Standard deviation. A measure of dispersion around the mean. In a normal distribution, 68% of cases fall within one standard deviation of the mean and 95% of cases fall within two standard deviations. For example, if the mean age is 45 with a standard deviation of 10, then 95% of the cases would be between 25 and 65 in a normal distribution. Standard error. A measure of how much the value of the mean may vary from sample to sample taken from the same distribution. The standard error of the sample mean can be used to estimate a mean value for the population as a whole. In a normal distribution, 95% of the values of the mean should lie in the range of plus and minus two times the standard error from the mean. Additionally, the standard error can be used to roughly compare the observed mean to a hypothesized value of another mean (that is, you can conclude the two values are different if the ratio of the difference to the standard error is less than -2 or greater than +2). Variance. This is the sample variance, which is a measure of dispersion around the mean, equal to the sum of squared deviations from the mean divided by one less than the number of cases. The sample variance is measured in units that are the square of those of the variable itself. In the following table, the first figure in each cell is the count, the second is the sum of the visits numeric variable, and the third is the mean value of the visits numeric variable.

103 89 Changing Cell Contents Figure 5-7 Table showing counts and total and mean number of visits When IBM SPSS Data Collection Survey Reporter calculates counts in a unweighted table, it increments the count in each cell by one each time it finds a case that satisfies the conditions that define the cell. In the above table, the count for the Yes cell of the General knowledge and education row has a value of 10 because there were 10 respondents who chose both the Yes category of the biology question and the General knowledge and education category of the expect question, and who pass the filter on the table. When you choose to base cell contents on the sum of a numeric variable, instead of incrementing each cell by one when it finds a case that satisfies the cell conditions, Survey Reporter increments the cell by the value held in the numeric variable for that case. If we look at the Yes cell of the General knowledge and education row again, we can see that the 10 respondents in the cell made a total of 34 previous visits to the museum. The mean shows the mean value of that variable for the respondents in the cell. The mean in the same cell is 3.40, which is what you get when you divide the total number of visits (34) by the number of respondents (10). The above table is filtered to exclude respondents who did not answer the question on which the visits variable is based.

104 90 Chapter 5 The next table is unfiltered and if we look at the Yes cell of the General knowledge and education row again, we can see that the mean is shown as The number of visits is still 34, but there are now 25 respondents in the cell, so the mean appears to be incorrect. This is because Survey Reporter calculates the means by dividing the sum by the number of respondents in the cell who answered the question on which the numeric variable is based, and not by the total number of respondents in the cell. In this cell, as in most cells in the unfiltered table, these two values are different. Figure 5-8 Unfiltered table showing counts and total and mean number of visits xpected Values and Residuals xpected values show the count or sum of a numeric variable that would be expected in the cell if the row and column variables were statistically independent or unrelated to each other. Residuals show the difference between the count or sum ofanumericvariableandtheexpected values. Large absolute values for the residuals indicate that the observed values are very different from the predicted values. In the following table, the first figure in each cell is the count, the second is the expected value, and the third is the residual.

105 91 Changing Cell Contents Figure 5-9 Table showing counts, expected values, and residuals Looking at this table, we can see that the General knowledge and education shows the biggest discrepancy between the actual counts and the expected values in both the Yes and No columns. However, the actual count is less than the expected value in the Yes column and this is reflected in the negative residual value and the actual count is greater than the expected value in the No column and this is reflected in the positive residual value.

106 Filtering Your Results Chapter 6 You can create filters to restrict the cases that are included in a table. For example, suppose you want to create a table that shows information about female respondents only. One way to do this is by filtering the table on the Female category of the gender variable. You can create simple or very complex filters. For example: You can define a condition that includes or excludes one or more categories in a variable. For example, you can select respondents who answered Yes to the question Do you hold a biology qualification? You can combine conditions using more than one variable. For example, you can select respondents who hold a biology qualification (biology variable) and have visited the museum more than 10 times (visits variable). You can specify how multiple conditions are to be combined. For example, you can specify that both of the filter conditions must be true for a respondent to be included in the table or you can specify that either one or other of the conditions must be true. For a comparison between filtering and other methods of removing information from your tables, see Removing categories from a variable. Types of filter You can use the following types of filter: Table Filters These apply to a particular table. You can also save filters that you have created for a particular table so that you can apply them to other tables. Global Filters These are filters that apply to all tables in the table document. Interview filters These apply to all tables and select respondents based on the interview status. This is useful when working with IBM SPSS Data Collection Interviewer Server data, because you can, for example, set up an interview filter to exclude test data and interviews that timed out. When more than one filter applies to a table (for example, a table filter and a global filter), they are combined using the And operator. This means that cases will be selected only if they meet the criteria of all of the filters. Creating a Filter You can create filters to restrict the cases that are included in a table. Select the table for which you want to define a new filter. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

107 93 Filtering Your Results Figure 6-1 Selecting a table Select the Filter pane: Figure 6-2 The Filter pane In the Filter description field, enter a description for the filter. This will appear as a header in the Results pane. It is a good idea to include the filter conditions in the description, so that you can see at a glance what the filter shows when you view the results. If you are working with hierarchical data, you also need to set the level at which you want the filter to operate. For more information, see the topic Filtering Hierarchical Data in Chapter 11 on p In the Variables pane, select the variable you want to use as a filter. Drag the variable onto the filter area: Figure 6-3 adding a filter variable Setupaconditionforthefilter; for example, for a categorical variable you can specify that only responses containing a specific category are included in the results. The type of condition you can set up varies according to the type of variable. For more information, see the topic Filter Conditions on p If required, you can add further conditions. For more information, see the topic Adding Multiple Conditions to a Filter on p The filter condition is applied to the table as soon as you switch to another pane. Press F5 to generate the results and display the table. diting a Filter You can edit an existing filter on a table to change or remove conditions. Select the table that contains the filter.

108 94 Chapter 6 Figure 6-4 Selecting a table Select the Filter pane: Figure 6-5 The Filter pane To edit an existing condition, use the drop-down boxes in the Filter pane to select new criteria for the condition. To delete a condition, highlight the variable in the Filter pane and press the Delete key. If you delete the only variable in a filter, the filter is removed from the table. You can also add new variables to create complex filters. For more information, see the topic Adding Multiple Conditions to a Filter on p Deleting a Filter You can delete a filter that you have added to a table. To delete a filter, you must delete all the variables on the Filter pane for that table. Select the table that contains the filter. Figure 6-6 Selecting a table Select the Filter pane: Figure 6-7 The Filter pane Click or Shift+click to highlight all the variables on the Filter pane. Choose the Delete button on the toolbar: Figure 6-8 Delete button

109 95 Filtering Your Results Saving a Filter You can apply a filter to the current table, or you can save the filter for use in other tables. To save a filter in the current table Table filters are automatically applied to the current table when you click away from the Filter pane, and are saved when you save the table document (.mtd) file. To save a filter for use in other tables You can save a filter that you create on one table for use in other tables, by saving the filter as a variable. The variable then appears in the Variables pane and you can add it to the Filter tab for another table. Create the filter in the first table where you want it to apply. From the Filter menu, choose Save Filter As. The Save Variable As dialog box appears. nter a name and description for the new variable. nsure that the variable name conforms to the IBM SPSS Data Collection Survey Reporter Naming Conventions. Choose OK. The filter is applied to the current table, and the new filter variable is added to the Variables pane. The filter appears as an edited boolean variable: Figure 6-9 Filter variable icon You can then apply the filter to other tables in the table document. For more information, see the topic Applying a Filter Variable to Another Table on p. 95. Applying a Filter Variable to Another Table When you save a filter as a variable, you can apply it to any other table. You can also use a filter variable as a global filter. Filter variables are saved as boolean variables, which means that they can be used in one of two ways, so if you find it useful to do so, you can use the same filter variable to exclude the selected responses in one table and to include only those responses in another table, as shown below. To apply a filter variable to another table Create and save the filter variable as described in Saving a Filter.

110 96 Chapter 6 In the Tables pane, select the table to which you want to apply the filter: Figure 6-10 Selecting a table Select the Filter pane: Figure 6-11 The Filter pane In the Variables pane, select the filter variable, and drag and drop it onto the filter area. The variable appears with the default condition. Figure 6-12 Filter variable added to Filter tab If required, you can add further conditions. For more information, see the topic Adding Multiple Conditions to a Filter on p The filter condition is applied to the table as soon as you switch to another pane. Press F5 to generate the results and display the table. To apply a filter variable using the inverse condition As filter variables are boolean variables, you can use the same filter variable in one of two ways, by selecting is true or is false in the drop-down list. If you select is true, thefilter is applied exactly as it was set up. If you select is false, thefilter has the opposite effect. For example, suppose you have a filter variable called Aged17AndOver that has the condition: Not age.containsany({1116_years}) You can set the filter condition to filter out responses for under 16s by using the default setting: Aged17AndOver is true Alternatively, you can use the same filter variable to filter out the responses for 17 years and over, by setting the filter condition to: Aged17AndOver is false

111 97 Filtering Your Results Setting the Level for a Filter By default, the data is analyzed at the top level. If you are using the hierarchical view of the data you may sometimes need to change the level of the data. For more information, see the topic Filtering Hierarchical Data in Chapter 11 on p To set the level for a filter Select the table for which you want to define a new filter. Figure 6-13 Selecting a table Select the Filter pane: Figure 6-14 The Filter pane In the Level drop-down list on the Filter toolbar, select the level at which you want to analyze the data. Bulk updating table filters Starting with version 6.0.1, IBM SPSS Data Collection Survey Reporter allows you to bulk update the filters for multiple tables. When you select multiple tables, that have the same filters, the selected tables will display as a single table. xpression and level changes for the displayed filter will apply to all selected tables. When the selected, multiple tables have different filters, the Multiple filters place holder will display for the filter.

112 98 Chapter 6 Figure 6-15 Multiple filter bulk update The Multiple filters place holder indicates that the selected table filters have differing expressions or levels. The place holder can only be replaced or deleted. Replacing the Multiple filters place holder You can replace the place holder by selecting different variables and clicking Replace. After clicking Replace, allfilters for the selected tables will be replaced with the selected variables and all filters will be set to the top level. Deleting the Multiple filters place holder You can delete the Multiple filters place holder by selecting the place holder and pressing the Delete key. After pressing Delete, the filters are cleared for all selected tables. Advanced multiple table filter conditions The Filter pane displays multiple table filters in a graphical format. The full filter expression displays in the Filter Syntax pane at the bottom of the screen. The place holder is identified in the expression as %Multiple filters%. Using the tables displayed in the image above as an example, selecting three tables that have different filters will display the following in the Filter Syntax pane: %Multiple filters% The %Multiple filters% place holder can only be removed or replaced in the Filter Syntax pane. Click Apply to validate the current syntax. If the syntax is valid, the Filter pane will automatically update to display the filter conditions. If the syntax is not valid, an error will display. Click Cancel to return the previously applied syntax.

113 99 Filtering Your Results Table Filters Table filters apply to a specific table. You use the Filter pane to define new filters for your tables andtomodifyexistingfilters. You can also save filters to use as variables when you create tables. In the top part of the pane you create a description for the filter. To create a filter, you select variables from the Variables pane and add them to the Filter pane. For more information, see the topic Creating a Filter on p. 92. The right side of the pane varies according to the type of variable you have selected. You use this area to define the filter condition for the variable. For more information, see the topic Filter Conditions on p Below this section is a toolbar, and in the Filter Syntax pane at the bottom of the screen are details of the conditions you have already defined. You can select a condition to change or remove it. For more information, see the topic Adding Multiple Conditions to a Filter on p The Filter menu is available when the Filter tab is visible. It provides the following features (these are also available as buttons on the Filter toolbar): Save Filter As. Saves the filter as a variable. It can then be applied to other tables. Move up. Moves the selected filter condition(s) up the list of conditions. Move down. Moves the selected filter condition(s) down the list of conditions. Group. Groups the selected filter conditions. Ungroup. Ungroups the selected filter conditions. xpand Categories. Displays a dialog box for selecting categories from a categorical variable or categorical grid variable, in cases where there are too many categories to display in the Filter tab without scrolling. Level. Selects the level of the filter. This is relevant only if you are using the hierarchical view of the data. Note that if there is another filter defined for a table, there are restrictions on which level you can choose for a new filter. For more information, see the topic Setting the Level for a Filter on p. 97. Category Selection Use the Category Selection dialog box to help you select categories to include in a filter condition, in cases where there are too many categories to display in the Filter tab without scrolling. To open the Category Selection dialog box, first select a categorical variable or categorical grid variable in the Filter (or Global Filter) tab, then choose Filter > xpand Categories

114 100 Chapter 6 from the menu, or choose the xpand Categories button on the Filter toolbar: Figure 6-16 xpand Categories button The dialog box contains a list of all the categories in the selected variable. You can resize the dialog box if necessary to show more categories. Check the boxes for any categories you want to include in the filter condition. Alternatively, if you want to select most of the categories, you can check the Select all box, then uncheck the individual categories that you do not want to include. Choose OK to save your changes and return to the Filter tab. Global Filters A global filter is a filter that is applied to all tables in the table document. You can define one global filter in any table document. You use the Global Filter pane to define global filters and to modify existing filters. You can also save filters to use as variables when you create tables. The Global Filter pane is displayed instead of the Filter pane when you select the table document (instead of an individual table) in the Tables pane. Figure 6-17 Selecting the table document in the Tables pane In the top part of the pane you create a description for the filter. To create a filter, you select variables from the Variables pane and add them to the Filter pane. For more information, see the topic Creating a Filter on p. 92. The right side of the pane varies according to the type of variable you have selected. You use this area to define the filter condition for the variable. For more information, see the topic Filter Conditions on p Below this section is a toolbar, and in the Filter Syntax pane at the bottom of the screen are details of the conditions you have already defined. You can select a condition to change or remove it. For more information, see the topic Adding Multiple Conditions to a Filter on p The Filter menu is available when the Filter tab is visible. It provides the following features (these are also available as buttons on the Filter toolbar): Save Filter As. Saves the filter as a variable. It can then be applied to other tables. Move up. Moves the selected filter condition(s) up the list of conditions. Move down. Moves the selected filter condition(s) down the list of conditions.

115 101 Filtering Your Results Group. Groups the selected filter conditions. Ungroup. Ungroups the selected filter conditions. xpand Categories. Displays a dialog box for selecting categories from a categorical variable or categorical grid variable, in cases where there are too many categories to display in the Filter tab without scrolling. Level. Selects the level of the filter. This is relevant only if you are using the hierarchical view of the data. Note that if there is another filter defined for a table, there are restrictions on which level you can choose for a new filter. For more information, see the topic Setting the Level for a Filter on p. 97. Interview Filter. Displays the Interview Filter dialog box, where you can define interview filters. IBM SPSS Data Collection Global Filters A Data Collection global filter is a user-level or role-level filter that controls access to case data in a project. To view the IBM SPSS Data Collection global filter defined for the current project, click the toolbar icon or go to: Filter > Data Collection Global Filter The Data Collection global filter option is only available if a Data Collection global filter exists for the project. Data Collection global filters are defined using the User Administration activity in IBM SPSS Data Collection Interviewer Server Administration. For details, see the Interviewer Server Administration User s Guide. Interview Filters An interview filter is a special global filter based on the status of data collected using IBM SPSS Data Collection Interviewer Server. You can change the settings for the interview filter using the Interview Filter dialog box. For example, you can apply a filter to display only completed interviews, or to display test interview results. To open the Interview Filter dialog box, select the Global Filter pane and choose Filters > Interview Filter or choose the Interview Filter button. Fields on the Interview Filter Dialog Box Respondent data only. Select this option if you want to include only data from real interviews. Test data only. Select this option if you want to include only test data. All data. Select this option if you want to select test data and real interview data.

116 102 Chapter 6 Filter on collection time. Check this box to restrict the data to that collected within a specific time period, and use the drop-down list boxes to select the range of dates. Interview status. Use the check boxes in this section to select cases on the basis of the outcome of the interview and whether the interview is marked as active (which generally means it is still in progress). You can select one or more options in this section. The options are: Completed successfully Active/in progress Timed out Stopped by script Stopped by respondent Interview system shut down Reviewed Signal (terminated by a signal statement in the script) Default Interview Filter By default, the interview filter includes test and real data in completed interviews. Changing an Interview Filter If you are using data collected using IBM SPSS Data Collection Interviewer Server, you can change the interview filter to view only the type of data you are interested in. For example, you may want to analyze data only from surveys that have been completed, and you may want to exclude any test data that has been collected. To add an interview filter Select the table document in the Tables pane: Figure 6-18 Selecting the table document in the Tables pane From the menu, choose Filters > Interview Filter In the Interview Filter dialog box, select the interview filter conditions. For example, if you want to see data only from completed surveys taken by real respondents (rather than test data), select the Respondent data only and Completed successfully options. Choose OK to save the filter conditions and close the dialog box.

117 103 Filtering Your Results Filter Conditions A filter defines one or more conditions for example, that the respondent s gender must be male and age must be over 45. Regardless of how you define your filter, internally the conditions are expressed as a conditional expression (for example, gender = {male} And age > 45 ). A conditional expression returns a value of true or false for each case. When you generate a table that has a filter applied to it, IBM SPSS Data Collection Survey Reporter applies the expression to each case. If the result is true, the case is selected and included in the table. If the result is false, the case is not selected and is excluded from the table. In a simple filter, such as the one described above, it is quite easy to see which cases pass the filter. In more complicated filtersitisnotalwayssoobvious. For example in a filter that defines certain categories that are to be excluded, only cases that are not in those categories pass the filter. For example, if the variable stores the respondent s gender, you might want to specify that the gender must be female. How you define the conditions depends on the variable s type: Single Response Variables Multiple Response Variables Numeric Variables Text Variables Boolean Variables Date Variables Categorical Grids The conditions must be based on the values that are actually stored in the variables. For example, when you filter on a categorical variable, you can base the condition on the responses to that variable, but you cannot base the conditions on any statistical elements that you have defined for the variable using the dit Variable window. Similarly, when you filter on a numeric variable, you must base the filter condition on the raw numeric values stored in the variable and you cannot reference any bands that you have set up for the variable on the Banding dialog box. The reason for this is that editing a variable changes how the variable will appear when you include it on the side or top of a table. It does not actually define the structure of the variable. Setting up Conditions for Single Response Variables Figure 6-19 Single response variable icon When you add a single response variable to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable. Select the categories you want to base the condition on and select the option from the drop-down list box that you want to apply: includes any of these. Select this option if you want to include respondents who chose at least one of the selected categories.

118 104 Chapter 6 includes none of these. Select this option if you want to exclude respondents who chose any of the selected categories. has a value. Select this option to include cases where a value exists for the selected variable. has no value. Select this option to include cases where there is no value for the selected variable. This includes cases where a particular survey question was skipped, for example. Setting up Conditions for Multiple Response Variables Figure 6-20 Multiple response variable icon When you add a multiple response variable to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable. Select the categories you want to base the expression on and select the option from the drop-down list box that you want to apply: includes any of these. Select this option if you want to include respondents who chose at least one of the selected categories. includes none of these. Select this option if you want to exclude respondents who chose any of the selected categories. includes all of these. Select this option if you want to include respondents who chose all of the selected categories. includes exactly these. Select this option if you want to include respondents who chose all of the selected categories and no others. includes at least. Select this option if you want to include respondents who chose at least a specified number of the selected categories. Specify the number in the text box. includes at most. Select this option if you want to include respondents who chose no more than aspecified number of the selected categories. Specify the number in the text box. is between. Select this option if you want to include respondents who chose a restricted number of the selected categories; for example, who chose between two and five categories. Specify the numbers in the text boxes. The first number should be smaller than the second number. has a value. Select this option to include cases where a value exists for the selected variable. has no value. Select this option to include cases where there is no value for the selected variable. This includes cases where a particular survey question was skipped, for example. Note: IBM SPSS Data Collection Survey Reporter does not include null values in the calculation of the base. For example, if a table is created with only one museums variable on the side and the filter museumsisnullis set, the base will display as a hyphen - character, instead of displaying the count of null museums. If there is a need to include the variable null values, add a user defined element to the axis expression. For the previous example, adding an element with expression 'mpty' expression('museumsisnull')in the museums variable will display the count of null museums. (See the The Base Calculation topic in the IBM SPSS Data Collection Survey Tabulation User s Guide for details.)

119 105 Filtering Your Results Setting up Conditions for Numeric Variables Figure 6-21 Numeric variable icon When you add a numeric variable to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable. nter a value in the text box and select the required operator from the drop-down list box. The full list of operators is: is less than. Select this option if you want to include cases for which the value is less than the specified number. nter a number in the adjacent field. is less than or equal to. Select this option if you want to include cases for which the value is less than or equal to the specified number. nter a number in the adjacent field. is equal to. Select this option if you want to include cases for which the value is equal to the specified number. nter a number in the adjacent field. is not equal to. Select this option if you want to include cases for which the value is not equal to the specified number. nter a number in the adjacent field. is greater than or equal to. Select this option if you want to include cases for which the value is greater than or equal to the specified number. nter a number in the adjacent field. is greater than. Select this option if you want to include cases for which the value is greater than the specified number. nter a number in the adjacent field. is between. Select this option if you want to include cases for which the value is between the specified numbers. nter two numbers in the adjacent fields. is not between. Select this option if you want to include cases for which the value is not between the specified numbers. nter two numbers in the adjacent fields. has a value. Select this option to include cases where a value exists for the selected variable. has no value. Select this option to include cases where there is no value for the selected variable. This includes cases where a particular survey question was skipped, for example. Setting up Conditions for Text Variables Figure 6-22 Text variable icon When you add a text variable to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable. Select the option from the drop-down list box that you want to apply: includes. Select this option if you want to include cases for which the variable contains the specified text. nter the text in the text box. begins with. Select this option if you want to include cases for which the variable stores text that begins with the specified text. nter the text in the text box.

120 106 Chapter 6 ends with. Select this option if you want to include cases for which the variable stores text that ends with the specified text. nter the text in the text box. is empty. Select this option if you want to include cases for which the variable stores an empty or Null value or white space only. is not empty. Select this option if you want to include cases for which the variable stores an empty or Null value or white space only. is exactly. Select this option if you want to include cases for which the variable stores exactly what you specify in the text box. is different from. Select this option if you want to exclude cases that are identical to the specified text. nter the text in the text box. does not include. Select this option if you want to exclude cases for which the variable contains the specified text. nter the text in the text box. does not begin with. Select this option if you want to exclude cases for which the variable begins with the specified text. nter the text in the text box. does not end with. Select this option if you want to exclude cases for which the variable ends with the specified text. nter the text in the text box. has a value. Select this option to include cases where a value exists for the selected variable. has no value. Select this option to include cases where there is no value for the selected variable. This includes cases where a particular survey question was skipped, for example. Setting up Conditions for Boolean Variables Figure 6-23 Boolean variable icon When you add a boolean variable to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable. Select the option from the drop-down list box that you want to apply: is true. Select this option if you want to include cases for which the value is True. is false. Select this option if you want to include cases for which the value is False. has a value. Select this option to include cases where a value exists for the selected variable. has no value. Select this option to include cases where there is no value for the selected variable. This includes cases where a particular survey question was skipped, for example. Setting up Conditions for Date Variables Figure 6-24 Date variable icon When you add a date variable to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable.

121 107 Filtering Your Results Select an option from the drop-down list box: is before. Select this option if you want to include cases for which the value is before the specified date. Select a date in the adjacent field. is after. Select this option if you want to include cases for which the value is after the specified date. Select a date in the adjacent field. is equal to. Select this option if you want to include cases for which the value is equal to the specified date. Select a date in the adjacent field. is between. Select this option if you want to include cases for which the value is between the specified dates. Select a beginning and end date in the adjacent fields. is not between. Select this option if you want to exclude cases for which the value is between the specified dates. Select a beginning and end date in the adjacent fields. has a value. Select this option to include cases where a value exists for the selected variable. has no value. Select this option to include cases where there is no value for the selected variable. This includes cases where a particular survey question was skipped, for example. Then use the text boxes to enter the required date and time. When you choose the Between option, another set of text boxes are available for entering the second date and time. Setting up Conditions for Categorical Grid Variables Figure 6-25 Categorical Grid icon When you add a categorical grid to the Filter pane, the right side of the pane enables you to define a condition based on the selected variable. If the grid contains more than one variable, use the Field drop-down list box to select the variable you want to base the expression on. The variable and its iterations are then displayed in a grid table. Select the cells of the table on which you want to base the expression and then select the option from the drop-down list box that you want to apply: includes any of these. Select this option if you want to include respondents who chose at least one of the selected cells. includes none of these. Select this option if you want to exclude respondents who chose any of the selected cells. Advanced Filter Conditions This section contains information on creating advanced filter conditions, including: Adding Multiple Conditions to a Filter Grouping Filter Conditions diting a Filter Using the Filter Syntax Pane Changing the Filter Details in Table Headers

122 108 Chapter 6 Adding Multiple Conditions to a Filter You can combine a number of conditions to create complex filters. As you drag and drop each variable into the Filter pane, the pane builds the conditions that have been defined. Multiple conditions are combined with: the And operator, which means that all of the conditions must be true for a case to pass the filter. This is the default. Combine conditions with the And operator when you want cases to be selected if they satisfy all conditions. the Or operator, which means that cases will pass the filter if any or all of the conditions are true. Combine conditions with the Or operator when you want cases to be selected if they satisfy either or both of the conditions. Choose And or Or to add or replace the existing operator. Moving a Condition If you want to change the order in which a condition appears in the filter after you have added it, highlight the condition in the Filter pane and use the up or down arrow buttons on the Filter toolbar to move it to the correct location. Grouping Filter Conditions If you create complex filters with multiple conditions, you may want to change the order of precedence of the conditions. To do this, you can group conditions so that an And or Or operator applies to the group rather than to an individual condition. Once you have grouped two or more conditions, you also have the option to use the NOT operator. Selecting NOT means that the filter only includes cases where the grouped conditions are not true. To Group Conditions In the Filter pane, use Shift+click to select the conditions that you want to group, and choose the Group button on the Filter toolbar: Figure 6-26 Group button A box is displayed around the grouped conditions. Note: If you look at the expression in the Filter Syntax pane, you will also see that the grouped conditions are surrounded by parentheses (), for example: age.containsany({1116_years}) And (biology.containsany({yes}) Or before.containsany({no})) To ungroup conditions that you have previously added to a group, select the grouped conditions and choose the Ungroup button on the Filter toolbar.

123 109 Filtering Your Results Figure 6-27 Ungroup button The grouping is removed from the conditions. diting a Filter Using the Filter Syntax Pane In the Filter pane, the filter information appears in graphical format. You may have noticed that as you create a filter in this pane, the full filter expression is displayed in the Filter Syntax pane at the bottom of the screen. For example, if you create a filter to exclude respondents in the year age group, you will see the syntax: Not age.containsany({1116_years}) appear in the Filter Syntax pane. This is useful, for example, when you want to copy and paste the expression for use in a script or some other application. You can also edit the expression directly once you become familiar with the syntax. You can even use this pane to create a new filter from scratch. To Display the Filter Syntax Pane From the menu, choose View > Filter Syntax The pane appears at the bottom of the screen. You can resize it and move it around the IBM SPSS Data Collection Survey Reporter window as required. To dit the Filter xpression Place the cursor in the Filter Syntax pane and type in the expression for the filter, or edit the existing expression. You can use any expression that is supported by the IBM SPSS Data Collection Data Model, including the functions in the IBM SPSS Data Collection Function Library. To validate and apply the filter syntax, choose the Apply button. If the expression is valid, the Filter pane is automatically updated to show the filter conditions. If it is not valid, an error is displayed. If you make a mistake while editing the syntax, choose the Cancel button to return to the previously applied syntax. See the Function List for details of the functions available. See also the xpression valuation and Data Collection Function Library topics in the IBM SPSS Data Collection Scripting section of the IBM SPSS Data Collection Developer Library for further information on syntax. xamples: Creating Complex Filters using the Filter Syntax Pane You can use the Filter Syntax pane to edit filters that you have set up using the Filter pane. In addition, you can create complexfilter expressions that are not possible using the options available in the Filter pane. The following examples show how to create a number of complex filters.

124 110 Chapter 6 Note: If you create a filter using the Filter Syntax pane that it is not possible to create using the options in the Filter pane, the message: The filter expression could not be displayed is shown in the Filter pane when you choose the Apply button. This is as expected, and does not prevent the filter from being applied to the table. Include exactly these categories Suppose that you want to create a filter for the remember variable to include only people who remembered the Dinosaurs and Fossils galleries but no other galleries. Here is an example of thesyntaxtodothis: remember.containsall({dinosaurs,fossils}, True) The True parameter restricts the filter to respondents who chose Fossils and Dinosaurs and no other galleries. If you wanted to select respondents who chose both Fossils and Dinosaurs regardless of whether they chose any additional galleries, you can use the same syntax without using True (this option is equivalent to choosing the Includes any of these option in the Filter pane): remember.containsall({dinosaurs, Fossils}) Include at least 2 of these categories You might want to include only people who remembered two or more of the Dinosaurs, Fossils, and volution galleries, regardless of whether they remembered other galleries. Here is an example of the syntax to do this: remember.containssome({dinosaurs, Fossils, volution},2) Include between 2 and 3 of these categories Suppose that you want to create a filter to include only people who remembered at least two, but no more than three, of the Dinosaurs, Fossils, volution, Birds, or Mammals galleries (regardless of which of the remaining galleries they remembered). Here is an example of the syntax to do this: remember.containssome({dinosaurs, Fossils, volution, Birds, Mammals},2,3) If you want this filter to exclude people who remembered any other galleries, you can add the True parameter to this syntax: remember.containssome({dinosaurs, Fossils, volution, Birds, Mammals},2,3, True) Include at most 3 of these categories You might also want to create a filter to include only people who remembered up to three of the cology, Wildlife in Danger, Botany, Conservation, or Fossils galleries (regardless of which of the galleriestheyrememberedthatarenotonthislist).hereisanexampleofthesyntaxtodothis: remember.containssome({cology, Wildlife_in_Danger, Botany, Conservation, Fossils},, 3)

125 111 Filtering Your Results Again, if you want this filter to exclude people who remembered any of the other galleries not on this list, such as Dinosaurs or Whales, you can add the True parameter to this syntax: remember.containssome({cology, Wildlife_in_Danger, Botany, Conservation, Fossils},, 3, True) Include only 1 of these categories To create a filter to include only people who remembered the Dinosaurs gallery but not the Fossils gallery, or the Fossils gallery but not the Dinosaurs gallery, regardless of which of the remaining galleries they remembered, you can use the following syntax: remember.containssome({fossils, Dinosaurs}, 1, 1) Again, if you want this filter to exclude people who also remembered any of the other galleries, you can add the True parameter to this syntax: remember.containssome({fossils, Dinosaurs}, 1, 1, True) These examples use functions from the IBM SPSS Data Collection Function Library. For more information, see the topic Function List in Chapter 19 on p For full details, see the xpression valuation and Data Collection Function Library topics in the Data Collection Scripting section of the IBM SPSS Data Collection Developer Library. Changing the Filter Details in Table Headers By default, when you add a filter to a table the filter description is displayed in the table s left header. When you are creating complex filters it may be time-consuming to type in a complete description of all the filter conditions. Instead, you can change the table header to show the filter syntax instead of the description. You can also change details of the way that filters appear, and you can change the position in which the filter details are displayed. To change the header details to show the filter syntax Select the table for which you want to change the header information. Choose the Properties button on the toolbar: Figure 6-28 Properties button In the Table Properties dialog box, choose the Header/Footer tab. The tab displays the existing header and footer definitions for the table. By default, filter information appears in the left header position, after the table description: {TableDescription \n}{filters \p} The \p option indicates that the standard prefix Filters precedes the filter information.

126 112 Chapter 6 Place the cursor directly after the \p and type \e, so that the header appears as follows: {TableDescription \n}{filters \p\e} The \e option displays the filter syntax instead of the filter description. To move the filter details to a different header or footer position Select the text {Filters \p\e} in the left header and press Ctrl+X to cut it from the header position. Place the cursor in the header or footer position where you want the filter details to appear. Note: nsure that you place the cursor outside the curly braces {} of any existing headers or footers. Press Ctrl+V to paste the filter details into the new header or footer position. To save the setting for the table, choose OK.

127 Using variables Chapter 7 Variables are the building blocks that you use for building tables and defining filters. In a data set based on a questionnaire or survey, a variable generally corresponds to a question or a part of a question, and records the question text and stores one answer, or set of answers, for each respondent who answered the question. However, some variables store other information, like a serial number or weighting details. The basic unit of analysis for which measurements are taken is called a case. Inadatasetbased on a survey, a case generally corresponds to a respondent. In a data set that is not based on a survey, the variables store characteristics that have been measured. Variables fall into a number of different groups, based on the type of data the variable stores, the type of question the variable is based on, and the way the variable is used. This section provides an introduction to the main types of variable. You can see all the variables used in your survey data file in the Variables pane, which by default appears at the left of the IBM SPSS Data Collection Survey Reporter window. An icon beside each variable helps you quickly identify its type. For a full list of variable types and their icons, see Variable Types. Note: Survey Reporter reads the definitions of the variables from the metadata, which is often in the form of a questionnaire definition or metadata (.mdd) file. The metadata defines the structure of the data and stores question and category texts in one or more language. Survey Reporter only accesses the stored responses when necessary (for example, when you generate your tables). The response data is called case data. Variable type overview Variables fall into a number of different groups based on the type of data the variable stores, the type of question the variable is based on, and the way the variable is used. The following table lists the different variable types and the icons that represent them. Icon Type Single response variable. A categorical variable that can have only one value for each case, such as a variable based on a question that requires the respondent to choose one answer from a predefined set of answers. An example is the question "Have you visited this museum before?" to which the respondent must answer "Yes" or "No". Also known as single categorical. For more information, see the topic Categorical variables on p Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

128 114 Chapter 7 Icon Type Multiple response variable. A categorical variable that can have more than one value for each case for example, a variable based on a question to which the respondent can choose several answers from a predefined set of answers. A typical example is the question "What do you remember seeing in the museum today?" in response to which the respondent can select any number of items in a list. Also known as multiple categorical. For more information, see the topic Categorical variables on p Numeric variable. A variable that stores a numeric value for each case. A numeric variable can store an integer or a real value. For more information, see the topic Numeric variables on p Text variable. A variable that contains data that is text, such as names and addresses or responses to open-ended questions. For more information, see the topic Text variables on p Date variable. A variable that stores date and time information. Loop. Aloopdefines a set of questions that are to be asked more than once. In a categorical loop, the number of times the loop is to be iterated (and therefore the number of times that the set of questions in the loop are to be asked) is controlled by the categories in a category list. For example, the set of questions can be asked for each product in a product list. In a numeric loop, the number of times the loop is to be iterated is controlled by a numeric expression. For more information, see the topic Loops and grids on p xpanded loop. When you are using a hierarchical view of the data, all loops are represented hierarchically as levels. However, when a loop is defined as expanded, it can also be viewed in an expanded (flattened) format as well, which means that you use it to create grid tables and you can select individual slices of the loop. For more information, see the topic Loops and grids on p Grid. A special type of loop in which all of the iterations are presented simultaneously to the respondent in a grid format. Grid questions often ask respondents to choose a rating on a predefined scale for a number of products in a list. Grids can be categorical or numeric. For more information, see the topic Loops and grids on p. 120.

129 115 Using variables Icon Type Boolean variable. A special type of integer variable that can contain values of True or False. Also called a Yes/No variable. For more information, see the topic Boolean variables on p Compound. Group for presentation purposes a number of related questions that share a category list. A compound is not the same as a grid, although a compound may contain one or more grids. For more information, see the topic Blocks and compounds on p Block. Groups one or more questions into a block. For more information, see the topic Blocks and compounds on p Weighting variable. A special numeric variable that has been set up to weight the data. You use weighting when you want the figures in your table to reflect your target population more accurately than the actual figures do. For example, suppose your target population consists of 57% women and 43% men, but you interviewed 50% women and 50% men for your survey. By applying weighting, you can make the women s figures count for more than the men s figures, so that they more accurately reflect the gender distribution in the target population. For more information, see the topic Applying Weighting in Chapter 10 on p System variable. Standard variables that are present in most data sets to store standard information, such as the respondent s serial number, the mode of data collection used, the version of the questionnaire used to collect the data, etc. Some data sets (such as databases) do not have system variables. System variables can be of different variable types including blocks, categorical, numeric, grids, etc. dited variable. This can be an existing variable that has been edited or a new variable that has been created from other variables. For example, you can edit a categorical variable by combining categories, or you can create a numeric variable to show the sum of the values stored in two or more other numeric variables. In some cases the edits to the variable may have been made outside IBM SPSS Data Collection Survey Reporter, so the variable has an edit symbol when you first open the survey data. dited variables can be based on variable types such as categorical, numeric, text, date, and boolean variables. Filter variable. This is a variable that has been created by saving a filter as a variable. Table variable. This is a variable that has been created from all the variables on the top or side of the table using the New Variable from Side/Top option.

130 116 Chapter 7 Icon Type Information variable. This contains instruction text for use when filling in the questionnaire. It cannot be included in analyses. Database Simple variable. This renders as a single response categorical variable. The categories are not defined in a list but are instead stored in a database. Categories are generated in derived variables when performing database categorization. The derived variable is generated as a helper field. Database Multiple variable. This renders as a multiple response variable. The categories are not defined in a list but are instead stored in a database. Categories are generated in derived variables when performing database categorization. The derived variable is generated as a helper field. Database Array variable. This renders as a loop/grid. Iterations are not definedinalistbutare instead stored in a database. Iterations are retrieved from a database. The derived variable is generated under the Array.Fields collection and stores the iterations when performing database categorization. Categorical variables Figure 7-1 Single response categorical variable Figure 7-2 Multiple response categorical variable A categorical variable stores one or a limited number of distinct values for each respondent. Categorical variables are generally based on questions that have a predefined list of possible responses, known as categories. For example, the age variable in the Museum sample data set stores the responses to the following question. This question has eight categories, which represent the possible responses: Figure 7-3 Single response question The age variable is called a single response variable because when a respondent answers the question, he or she must choose only one response from the list of categories.

131 117 Using variables In some categorical questions, the respondent can choose more than one category from the list of categories. A variable that stores the responses to this type of question is called a multiple response variable and it can store more than one response for each respondent. Here is an example of a multiple response question: Figure 7-4 Multiple response question NoticethatthisquestionhasacategorywiththetextOther. If a respondent has visited museums that are not in the list of categories, he or she can select this category and write the museum names in the space provided. This type of category is called an Other Specify category and the open-ended responses to this question are stored in a text variable called an Other Specify variable that is associated with the main categorical variable. Variables that are associated with a main variable and hold additional information are called helper variables. In a categorical variable, there is one category for each response in the question on which it is based. Sometimes categorical variables have additional items, for example, representing the base or the mean value. You can add items to variables for use in your tables. However, in some data sets (particularly IBM SPSS Quanvert databases) the variables actually have these additional items built into the structure of the variable. How do categorical variables store the responses? IBM SPSS Data Collection Survey Reporter accesses the data through the IBM SPSS Data Collection Data Model, which presents data in a consistent way regardless of the underlying data format. It is not necessary to understand how the Data Model represents the responses stored in a categorical variable when you are simply building tables or defining simple filters. However, you will find it helpful to understand it if you want to use some of the advanced features, such as using advanced expressions to define filters. The Data Model assigns a unique numeric (integer) value to each unique category full name in the data set. These unique values are called mapped category values. Category full names must be unique within a question, but the same full name can be used in different questions. For example, categories called Yes and No can be used in several questions, and will have the same mapped value in each one. By default, the Data Model presents the responses to a categorical question as a string, in which the mapped values are formatted within braces, ({ }) and separated by commas (,). For example, the response to a single response question might be {24} and the response to a multiple response question might be {31,36,43}, where 24, 31, 36, and 43 are the mapped values of the chosen categories. However, provided a metadata source is available, the Data Model can also present the

132 118 Chapter 7 responses using the category names rather than the mapped values. Our example responses might then appear as {female} and {dinosaurs,insects,human_biology}. When you refer to specific responses in, for example, a filter expression, you should normally use the category names and not the mapped values. The following table provides examples of doing this. Use the category names Rather than the mapped values gender = {female} gender = {24} remember = {dinosaurs,insects,human_biology} remember = {31,36,43} Numeric variables Figure 7-5 Numeric variable A numeric variable stores one numeric value for each case. Numeric variables are often based on questions that ask How many? or How much? and require the respondent to give a numeric response. For example, in the Short Drinks sample data set, respondents are asked to enter their age as a numeric value rather than by selecting the category that represents their age group. When respondents answer the question, they enter a whole number. For example: Figure 7-6 Numeric question Sometimes you may want to group the numeric values stored in a numeric variable into categories. For example, you may want to create a table that shows the age data in age groups. The process of creating categories from a numeric variable is sometimes called banding and each category is called a band. Banding a numeric variable is similar to coding a text variable, but it is generally easier, because you can define the bands using numeric expressions. You can define the bands using IBM SPSS Data Collection Survey Reporter or you can create automatic bands (for example, ten equal bands starting at the minimum value and ending at the maximum value). For more information, see the topic Creating bands on p Numeric variables can be divided into two groups based on the type of numeric data they store: Long variables. These store one integer value for each case. Double variables. These store one real (decimal) value for each case.

133 119 Using variables Unable to Add Variable The Unable to Add Variable dialog displays when you attempt to add a numeric variable, with no axis expression, to an existing table or when youattempt to create a new table. The dialog provides the following options: Create Numeric Summary Click to add summary statistics to the numeric variable. For more information, see the topic Adding summary statistics to a numeric variable on p dit Variable... Click to launch the dit Variable dialog and specify the content of variables when they appear in your tables. For more information, see the topic dit Variable dialog boxonp Categorize... Click to launch the Simple Categorization dialog and perform simple, non-linguistic categorization of variables by converting Text, Date or Numeric variables, which cannot be directly used in table tabulation, to Categorical variables. For more information, see the topic Simple categorization on p Text variables Figure 7-7 Text variable A text variable stores one text value for each case. For example, a text variable may store the responses to an open-ended question. This is a question that asks respondents to answer a question in their own words. For example: Figure 7-8 Open-ended question Before analyzing the responses to an open-ended question, market researchers frequently code the responses into categories. For example, the responses to this question could be coded into the following categories: Figure 7-9 Coding categories

134 120 Chapter 7 A variable that stores the coded responses to an open-ended question is called a coding variable and like the Other Specify variables described in the topic on categorical variables, the coding variable is generally associated with the main text variable as a helper variable. Loops and grids Surveys and questionnaires often contain individual questions and sets of questions that are asked more than once. For example, questionnaires often contain grid questions that ask respondents to choose a rating on a predefined scale for a number of products in a list, and sets of questions that respondents are asked to answer for each product in a list of products or for each person in a household. Loops Figure 7-10 Loop The number of times the question or set of questions is to be asked can be controlled in three main ways: By the categories in a category list. For example, For each brand in the following list, please answer the following... By a numeric expression that has a known upper limit. For example, For each of the first three journeys you described earlier, please answer the following... By a numeric expression that has an unknown upper limit. For example, For each drink you consumed last week, please answer the following... ach of these constructions is a loop that defines the question or set of questions and the number of times they are to be asked (or, in more technical terms, the number of times the loop is to be iterated). When you analyze the data in IBM SPSS Data Collection Survey Reporter, whether the questions in the loop were asked simultaneously as a grid or sequentially (one after the other) is not really relevant.

135 121 Using variables To understand how it works, let s consider the following loop, which is presented here in a grid-like format: Figure 7-11 Numeric loop question This loop contains two questions, Name and Gender, which are asked up to 6 times. This means that the loop has 6 iterations. When the response data is presented in a non-hierarchical form, it is flattened and a separate variable stores the responses to each question in each possible iteration. In this example, there would be 12 variables (2 * 6). For example, if the loop is called MyLoop, the following variables would store the responses: MyLoop[1].Name MyLoop[2].Name MyLoop[3].Name MyLoop[4].Name MyLoop[5].Name MyLoop[6].Name MyLoop[1].Gender MyLoop[2].Gender MyLoop[3].Gender MyLoop[4].Gender MyLoop[5].Gender MyLoop[6].Gender These are the full names of the variables and they are constructed from the names of the loop and the questions inside the loop. Brackets ([ ]) are used to indicate an iteration and a single period (.) to indicate a parent/child relationship. This method of representing hierarchical data is simple and effective. However, it has some disadvantages, the most obvious one being that the number of variables is fixed. In our household example, this means that storage space is reserved for the responsestill not visiof six individuals in each household even though many households have fewer people. Conversely, responses cannot be stored for any additional people in large households. Another disadvantage is that performing summary calculations on the data can be difficult.

136 122 Chapter 7 Representing the case data hierarchically can be more flexible and provides advantages during analysis. The loop is then considered a level and the responses to the questions in the loop are stored in a separate hierarchical table named after the loop. In this example, the hierarchical table would contain two variables, one for each of the questions in the loop, and would store the responses to each iteration in a separate row. The full names of these variables would be: MyLevel[..].Name MyLevel[..].Gender Notice that two periods (..) are used in place of an iteration number, to indicate all iterations. xpanded loops Figure 7-12 xpanded Loop In some data formats, some loops can be represented both hierarchically and flattened. These loops are known as expanded loops. However, this is not possible when the maximum number of iterations has not been defined (these loops are sometimes referred to as unbounded loops). Grids Figure 7-13 Categorical grid Figure 7-14 Numeric grid

137 123 Using variables A grid is a special case of a loop, in which the iterations are controlled by a category list and when the grid question is asked, all of the iterations are presented simultaneously. In the Museum survey there is a grid question that asks respondents to rate the galleries in the museum: Figure 7-15 Rating grid question In this grid, the list of galleries is the controlling category list, the grid itself is called rating and the categorical question inside the grid is called column. The full names of the individual variables that store the flattened responses to the grid are: rating[{dinosaurs}].column rating[{conservation}].column rating[{fish_and_reptiles}].column rating[{fossils}].column rating[{birds}].column rating[{insects}].column rating[{whales}].column rating[{mammals}].column rating[{minerals}].column rating[{cology}].column rating[{botany}].column rating[{origin_of_species}].column rating[{human_biology}].column rating[{volution}].column rating[{wildlife_in_danger}].column rating[{other}].column These are sometimes referred to as grid slices.

138 124 Chapter 7 When the question or questions inside the grid are numeric rather than categorical, the grid is sometimes referred to as a numeric grid question. For example, in the Short Drinks sample data, there is a numeric grid question that asks respondents to enter the number of drinks of various types they consumed each day of the previous week: Figure 7-16 Numeric grid question In this example, the drinks are the iterations and the days of the week are numeric questions inside the loop. Boolean variables Figure 7-17 Boolean variable A Boolean variable stores a value of true or false for each case. Sometimes Boolean variables are based on a question (such as Doyouownacar?) that has only two possible answers. For example, Yes, which corresponds to true, and No, which corresponds to false. Boolean variables can include special variables that have been defined especially for use as filters. These variables are sometimes referred to as filter variables. Blocks and compounds Figure 7-18 Block Figure 7-19 Compound Blocks and compounds are used to group questions simply for presentation or organizational purposes. Unlike grids and loops, blocks and compounds do not define a hierarchy in the case data, although they do appear as expandable items in the Variables pane.

139 125 Using variables A block is used to group a list of questions. For example, a block called Demographics might be used to group the demographic questions in a questionnaire. Three blocks (Respondent, DataCollection, DataCleaning) are used to group the system variables. A compound is used to group a number of questions that share a category list. Compounds are typically used in paper questionnaires. Here is an example: Figure 7-20 Compound question You can see the variables that are nested inside a block or compound by clicking to expand it in the Variables pane. You can use the variables inside a block or compound in your tables in the normal way. diting variables You can change how variables appear in your tables in a number of ways. For example, you can add or remove categories, combine existing categories into new ones, and add summary statistics to tables. Whenyoueditavariable,youcandoitinoneoftwoways: edit a variable on a selected table, using the Design pane edit a variable on all tables, using the Variables pane When you edit a variable on a selected table, the changes you make apply only to that table. When you edit a variable in the Variables pane, the changes you make apply to other tables that you create in the same table document (.mtd) file. diting a variable on a selected table Double-click the variable name on the side or top of a table on the Design pane.

140 126 Chapter 7 Figure 7-21 Selecting a variable on a table Alternatively, select the variable in the Design pane and from the menu, choose Variables > dit Table Variable This displays the dit Table Variable window, where you can make your changes. diting a variable on all tables Double-click the variable in the Variables pane. Figure 7-22 diting a variable in the Variables pane Alternatively, select the variable in the Variables pane and from the menu, choose Variables > dit Variable This displays the dit Variable window, where you can make your changes. Unless otherwise stated, the topics in this section begin by selecting variables in the Variables pane, so that the changes apply to all tables. However, if you want to restrict your changes to a single table, select the variable on the table using the Design pane instead.

141 127 Using variables Changing the description for a variable You can choose whether to show variable names or descriptions (which are also called labels) in your tables. When you use variable descriptions, provided translations are available, you can select the language in which the descriptions are displayed. Changes apply to all tables. When using the variable descriptions, you may sometimes find that you want to change the description for a variable for example, to make it shorter so that it fits the available space better. Switching between variable names and descriptions Tools > Options In the Options dialog box, choose the Display tab. In the Display variables as drop-down, select Names or Labels. Choose OK to save changes and close the dialog box. Changing a variable s description In the Variables pane, select the variable that you want to change. From the menu, choose Variables > dit Variable This opens the dit Variable window. In the description field beneath the variable s name, type a new description. Choose Save and Close from the toolbar. Changing the description for a category You can choose whether to show category names or descriptions in your tables. Changes apply to all tables. When using the descriptions, you may sometimes find that you want to change a description, for example, to make it shorter so that it fits the available space better. Switching between category names and descriptions From the menu, choose: Tools > Options In the Options dialog box, choose the Display tab. In the Display categories as drop-down, select Names orlabels. Choose OK to save changes and close the dialog box.

142 128 Chapter 7 Changing a category description In the Variables pane, select the variable that you want to change. From the menu, choose Variables > dit Variable This opens the dit Variable window and displays a list of all the categories in the variable. Press F2, with the cursor positioned in a category description column for the category you want to change, and edit it as required. Choose Save and Close from the toolbar. Changing the variable description language Provided that translations are available in your survey, you can select the language in which the variable and category descriptions are displayed. Changing the variable description language From the menu, choose: File > Properties In the File Properties dialog box, choose the Advanced tab. The Variable description language drop-down contains a list of languages for which translations are available. Select the language you want to use. Choose OK to save changes and close the dialog box. If the language displayed in your tables does not change, this may be because you are displaying the names and not the descriptions for variables and categories. To change this: From the menu, choose: Tools > Options Choose the Display tab, and in the Display variables as and Displaycategoriesasdrop-downs, choose Labels. Choose OK to close the dialog box. Changing the order of categories in a variable You can change the order of the categories in a variable, so that they appear in a different order in tables. Changing the order of categories In the Variables pane, select the variable that you want to change.

143 129 Using variables From the menu, choose Variables > dit Variable This opens the dit Variable window and displays a list of all the categories in the variable. Clicktoselectacategorythatyouwanttomove. From the toolbar, choose the Move Up or Move Down button until the category is in the correct position. Repeat for any other categories you want to move. Choose Save and Close from the toolbar. Combining categories Sometimes it is useful to combine two or more categories into a single category. When you do this, you can choose whether to keep the original categories. For example, here is a table that has the remember variable from the Museum data set on the side of the table. This variable contains a list of 15 galleries; in this example, they have been combined into three new categories. Figure 7-23 Table showing remember by gender, with combined categories When you combine categories in a multiple response variable, the combined category shows the total number of respondents who chose one or more of the categories that make up the combined category and not the total number of responses. Combining categories In the Variables pane, select the categorical variable that you want to change. From the menu, choose Variables > dit Variable This opens the dit Variable window and displays a list of all the categories in the variable. Select the categories that you want to combine (use Ctrl+click or Shift+click to select multiple categories). From the menu choose Categories > Combine > Combine This replaces the selected categories with the new combined category.

144 130 Chapter 7 Note: If you want to retain the original categories as well as the combined categories, you can use the option: Categories > Combine > Combine and Keep This adds a new combined category but also retains the original categories in the table. If required, edit the default description for the new combined category. Repeat the last three steps for any other categories you want to combine. Choose Save and Close from the toolbar. Difference between Combine and Combine and Keep When performing a simple combine (or net), you are actually deleting some elements and adding a new combine (or net) element. Considering that the elements being combined (netted) are deleted, they are not included in the calculation. As a result, the calculations for some statistics cell items (such as mean) will be changed. When performing a combine (or net) and keep, you are simply adding a new combined (or netted) element. The default factor value of the new element is zero. Without setting a factor for the new element, the calculation result will be the same as before adding the element. If you set a factor value for the element, the statistics value changes because the newly added element is included in the calculation. Creating nets A net is a special item that shows the number of respondents who chose one or more from a group of categories. Nets are useful in multiple response variables in which the categories fall into a number of groups (such as favorable, unfavorable, and neutral). Nets enable you to find out how many people chose one or more responses in each group. (Subtotals would tell you the total number of responses that were chosen in each group, but not how many people chose those responses.)

145 131 Using variables IBM SPSS Data Collection Survey Reporter indents the categories that belong to the net. For example, here is a table that has the remember variable with the categories grouped into three nets on the side of the table: Figure 7-24 Table showing remember by gender, with categories grouped into nets Creating nets In the Variables pane, select the categorical variable that you want to change. From the menu, choose Variables > dit Variable This opens the dit Variable window and displays a list of all the categories in the variable. Select the categories that you want to include in the net (use Ctrl+click or Shift+click to select multiple categories). From the menu choose Categories > Combine > Net This replaces the selected categories with the new net category. Note: If you want to retain the original categories as well as the net categories, you can use the option: Categories > Combine > Net and Keep This adds a new net category but also retains the original categories in the table and allows variablestobeincludedintwoormorenets. If required, edit the default description for the net. Repeat the last three steps for any other nets you want to create. Choose Save and Close from the toolbar.

146 132 Chapter 7 Difference between Net and Net and Keep When performing a simple combine (or net), you are actually deleting some elements and adding a new combine (or net) element. Considering that the elements being combined (netted) are deleted, they are not included in the calculation. As a result, the calculations for some statistics cell items (such as mean) will be changed. When performing a combine (or net) and keep, you are simply adding a new combined (or netted) element. The default factor value of the new element is zero. Without setting a factor for the new element, the calculation result will be the same as before adding the element. If you set a factor value for the element, the statistics value changes because the newly added element is included in the calculation. Combining categories in a grid Grid questions frequently ask respondents to choose a rating on a predefined scale for a number of products in a list. Sometimes you may want to combine two ratings in a grid into a single rating, to create a Top Two Box. For example, this table uses the rating grid variable in the Museum data set. The Slightly interested and Very interested categories have been combined to form a new Top Two Ratings category. Figure 7-25 Table showing interest rating for galleries, with very interested and slightly interested categories combined Combining grid categories In the Variables pane, expand the grid or loop.

147 133 Using variables Select the variable that is inside the grid or loop. This variable is often called Column: Figure 7-26 xpanding the grid and selecting the variable From the menu, choose Variables > dit Variable This opens the dit Variable window and displays a list of the categories in the variable. Select the categories that you want to combine (use Ctrl+click or Shift+click to select multiple categories). From the menu choose Categories > Combine > Combine This replaces the selected categories with the new combined category. dit the default description for the new combined category. Choose Save and Close from the toolbar. Create a table using the grid variable. For more information, see the topic Creating tables using grid variables in Chapter 4 on p. 63. Creating summarized grids Often researchers and analysts want a summarized version of a grid question (a rating scale for example) where the top-two categories are combined for analysis. This is accomplished through standard variable editing (editing the categories of the grid question for example). However, there are times when a new view of the grid is required. For example, assume you wanted to tabulate each row by those people who were satisfied with a subject (i.e. per slice of a grid or iteration of a loop) against other key variables in the survey. Simply editing categories of the grid question would result in you having to manipulate countless grids and slices. Creating a summarized version of a grid prevents to need to maintain multiple grids and slices. Creating a summarized version of a grid Create a new categorical variable: Variables > New This opens the New Variable window. Insert a category: Categories > Insert Categories...

148 134 Chapter 7 This opens the Insert Categories window and displays a list of available categories. Make the category a User Defined item. Provide an appropriate category description in the Description field. Click dit Item... This opens the dit User Defined Item window that provides options for defining and modifying the expression for a user defined category. Select the whole grid and add to the canvas. Select the categories required for your grid question (for the row of the grid you are replicating). Notes: If you have a large grid, click Open Category to place the whole grid in a new window before trying to make your selections. When answering a different analysis question, you can select across grid slices or loop iterations as well as grid question categories. Click OK to return to the Insert Categories window. Click OK to return to the New Variable window. Insert any other new categories for the appropriate grid/loop items into your new variable. Save the new variable and exit the New Variable window. Add the new variable to your table(s). Creating bands Sometimesyoumaywanttogroupthevaluesinanumericvariableintocategories.Theprocess of creating categories from a numeric variable is sometimes called banding and each category is called a band. For example, the numeric visits variable in the Museum survey stores the number of times respondents have visited the museum before. Responses can contain any value from 1 to 100. To display this information on a table, you can specify a number of bands, and display one row or column for all responses that fall into each band. This table shows the responses in the visits variable grouped into four bands: Figure 7-27 Table showing visits by gender; visits is banded into four categories. You can use the Insert Bands dialog box to create automatic bands (for example, ten equal bands starting at the minimum value and ending at the maximum value) or you can define the bands individually.

149 135 Using variables Creating bands In the Variables pane, select the numeric variable for which you want to create the bands. From the menu, choose: Variables > dit Variable This opens the Insert Bands dialog box, with the dit Variable dialog behind it. Creating bands based on actual data values In the Insert Bands dialog box, choose the Get values from data button. The minimum and maximum values from the saved data are displayed in the From and To text boxes. Choose OK. To create a number of equal bands In the Insert Bands dialog box, enter the starting value for the firstbandinthefrom text box. nter the ending value for the finalbandintheto text box. nter the number of bands to create in the Number of bands text box. If the variable contains responses that use decimals, you can use the Number of decimals text box to set the number of decimal places to use for the bands. Choose OK to close the dialog box, then choose the Save button in the dit Variable dialog box to save your changes. Creating single bands individually In the Insert Bands dialog box, enter the starting and ending value for the first band in the From and To text boxes. Set the Number of bands to 1. If it is a real numeric variable, enter the Number of decimals. Choose OK. Repeat as necessary for each band you want to create. Choose Save and Close from the toolbar. Creating a category based on another variable Sometimes you may want to add a new category that is based on another variable. For example, in the Museum survey, you could add a category to the biology variable that selects respondents who entered a value greater than 4 when answering the question How many times have you visited the museum before today? (this the value in the visits variable).

150 136 Chapter 7 Figure 7-28 Table of interest by biology; biology variable shows additional category You can do this by adding a user-defined category to the variable. Adding a new category In the Variables pane, select the text variable that you want to change. From the menu, choose Variables > dit Variable This opens the dit Variable window and displays information about the variable. From the menu, choose Categories > Insert Categories This opens the Insert Categories dialog box. In the list of Available Items, select User-defined, and then choose the >> button to add it to the list of items to insert. Select the new category and edit the Description field to give it a meaningful description. With the category still selected, choose the dit item button. This opens the dit User-Defined Category dialog box. In the list of variables on the left of the dialog, select the variable that you want to base the category on, for example, visits, and drag it to the Filter area on the right of the screen. Use the features on the right side of the dialog box to define the expression for the category. For example, select Greater than from the drop-down list box and then enter 4 in the text box. When you have finished defining the category, choose OK to save the changes and return to the Insert Categories dialog box.

151 137 Using variables Then choose OK again to return to the dit Variable dialog box. If necessary, use the features in this dialog to make further changes to the variable. Choose Save and Close from the toolbar. Creating a category based on other categories Sometimes you may want to add a category that contains the results of a calculation based on the values in other categories. You can do this by adding a derived category to the variable. To create formula for the category, you can add or subtract the values in the other categories, or use a function from the IBM SPSS Data Collection Data Model. For example, in this table the age variable has a derived category called 55 or over, created by adding together the values in the years and 65+ years categories. Figure 7-29 Table showing category 55 or over calculated from two other categories Creating a derived category In the Variables pane, select the variable. From the menu, choose: Variables > dit Variable This opens the dit Variable window and displays details of the variable. From the menu, choose Categories > Insert Categories This opens the Insert Categories dialog box. In the list of Available Items, selectderived category and choose the >> button to add it to the Items to insert list. In the description field, replace the default description with the text that you want to appear on the table, for example, 55 or over. Choose the dit Item button to open the dit Derived Category dialog box and display a list of all the categories in the variable.

152 138 Chapter 7 Click and drag the years category to the text box on the right of the screen. Type a + symbol (optionally, include a space before and after the symbol to make it easier to read). Click and drag the 65+ years category onto the right of the screen after the + symbol. The expression should now look like this: 5564_years + 65_years Choose OK to close the dit Derived Category dialog box, then choose OK again to close the Insert Categories dialog box. Choose Save and Close to close the dit Variable dialog box. Adding summary statistics to a numeric variable Sometimes you may want to show a summary statistic of the values in a numeric variable (such as the mean, minimum, or maximum) rather than grouping the values into bands. For example, the visits variable in the Museum sample data set is a numeric variable that stores the number of times respondents have visited the museum before. You can show a summary of the values in the variable, as shown in the following table: Figure 7-30 Table showing visits by gender, with summary statistics mean, min, max and standard deviation Note: IBM SPSS Data Collection Survey Reporter does not automatically add summary statistics to numeric variables that do not have any bands or other statistics defined. You will need to manually set up these definitions if they do not already exist. The Unable to Add Variable dialog displays in cases where variables do not have statistics defined. In practice you might want to mix both approaches, to include bands and also a mean value. In that case you could create bands, as shown in Creating bands, then insert the statistics as described below. Adding summary statistics to a numeric variable In the Variables pane, select the numeric variable. From the menu, choose: Variables > dit Variable This opens the dit Variable window with the Insert Bands dialog box on top. Choose Cancel to close the Insert Bands dialog box.

153 139 Using variables From the menu, choose Categories > Insert Categories This opens the Insert Categories dialog box. In the list of Available Items, select the summary statistics you want to use. For example, select Minimum, Maximum, Mean, and Standard Deviation. Choose the >> button to add them to the Items to insert list. If required, edit the default description and decimal places for each inserted item. Choose OK to close the Insert Categories dialog box. This inserts the statistics into the list on the dit Variable window. By default, the statistics are based on the variable to which you are adding the categories. Choose Save and Close from the toolbar. Adding summary statistics to a categorical variable Sometimes you may want to add a summary statistic to a categorical variable, for example, to show the mean score in a rating question. When you do this, by default the statistic is calculated on the basis of factors associated with the categories. Alternatively, you can base the calculation on a specific numeric variable. A factor is a constant numerical value that is assigned to a category for use in statistical calculations. Factors are used when you want to base a statistic on the categories in a categorical variable rather than on a numeric variable. This is because statistics can be calculated on numeric data only and categories are not true numeric values. (Although the IBM SPSS Data Collection Data Model represents the responses to categorical questions as numeric values, these are in fact identifiers or codes and are not suitable for statistical analysis.) Adding a summary statistic to a categorical variable for all tables In the Variables pane, select the categorical variable. From the menu, choose: Variables > dit Variable This opens the dit Variable window. Select the item after which you want the summary statistic to appear. From the menu, choose: Categories > Insert Categories This opens the Insert Categories dialog box. In the list of Available Items, select the summary statistic that you want to use. For example, select Mean or Standard Deviation. Choose the >> button to add it to the list of items to insert.

154 140 Chapter 7 If required, edit the default description and decimal places for the inserted item. Choose OK to close the Insert Categories dialog box. This inserts the statistic into the list of items in the variable. By default, the statistic will be calculated based on factors assigned to the categories in the variable. To add factors: In the dit Variable dialog box menu, choose Categories > Add Factors In the Add Factors dialog box, enter a starting value and an increment, and choose OK. Factors are assigned to each category in the variable. The order in which the categories appear in the list determines the order in which the increments are applied. Choose Save and Close from the toolbar. Adding summary statistics to a grid Grid questions frequently ask respondents to choose a rating on a predefined scale for a number of products in a list. You can add summary statistics to these questions, for example, a mean to show the average rating, just like you can in any other categorical variable. Adding summary statistics to a grid In the Variables pane, expand the grid or loop. Select the variable that is inside the grid or loop. This variable is often called Column: Figure 7-31 xpanding the grid and selecting the variable From the menu, choose Variables > dit Variable This opens the dit Variable window and displays a list of the categories in the variable. Select the item after which you want the mean to appear. From the menu, choose: Categories > Insert Categories This opens the Insert Categories dialog box. In the list of Available Items, select the summary statistic that you want to use. For example, select Mean or Standard Deviation. Choose the >> button to add it to the list of items to insert.

155 141 Using variables If required, edit the default description and decimal places for the inserted item. Choose OK to close the Insert Categories dialog box. This inserts the statistic into the list of items in the variable. The statistic will be calculated based on factors assigned to the categories in the variable. To add factors: In the dit Variable dialog box menu, choose Categories > Add Factors In the Add Factors dialog box, enter a starting value and an increment, and choose OK. Factors are assigned to each category in the variable. The order in which the categories appear in the list determines the order in which the increments are applied. Choose Save and Close from the toolbar. Create a table using the grid variable. For more information, see the topic Creating tables using grid variables in Chapter 4 on p. 63. Displaying a snapshot of values for categories in a variable You can display a snapshot of the counts and percentages of the categories in a variable in the dit Variable dialog box. As you add, combine, or band categories in a variable, you can update the counts to see the results of your changes. Note: Another way to display snapshot information for a variable is to use TheVariablePreview Pane. Displaying counts for a variable In the Variables pane, double-click the variable, or from the menu, choose: Variables > dit Variable This opens the dit Variable window. The category values are updated and displayed in the Count and Percent columns. Updating counts for a variable When you edit categories in a way that changes the counts, for example, by combining a categories into a single new category, the values in the Count and Percent columns are displayed as??. To update the values: From the menu, choose: Categories > Update Counts or choose the Update Counts button: Figure 7-32 Update counts button

156 142 Chapter 7 Adding text rows to tables Sometimes you may want to display text or symbols in the cells of a table. For example, the following table (based on the mployee Data sample, available with the IBM SPSS Data Collection Developer Library) has an additional Currency row that displays the currency type, and a row that acts as a dividing line before the final row: Figure 7-33 Table of current salaries with currency and divider rows You can create text-only rows by adding a Column text item to a variable, and specifying the text to appear in the cells when the variable appears in the rows of a table. You can add the same text to each column of the new row, or you can enter different text in each column. In the above table, the first column of the row used as a divider contains different characters. The text appears only when the variable is on the side of a table. If you add the variable to the top of the table, only the heading text appears. Text-only rows are not displayed in charts. Note: If you want to append text to the contents of an existing cell, for example, to add a currency symbol, you can add a prefix orsuffix to the cell contents in the Table Properties dialog box. For more information, see the topic Adding and Removing Cell Contents in Chapter 5 on p. 81. Adding text rows to a table These instructions explain how to add text rows to a variable on a single table, rather than for all tables. This is because the text in the row may be specific to the categories in the variable on the top of the table and therefore inapplicable when tabulated with other variables. Create the table by adding the variables to the top and side of the table.

157 143 Using variables In the Design pane, select the variable on the side of the table: Figure 7-34 diting a table variable From the menu, choose Variables > dit Table Variable This opens the dit Table Variable window and displays information about the variable. From the menu, choose Categories > Insert Categories This opens the Insert Categories dialog box. In the list of Available Items, select Column Text, andchoosethe>> button to add it to the list of items to insert. In the Description field, enter the heading for the row, or remove the text to leave the heading cell blank. Choose OK to close the Insert Categories dialog box. In the dit Table Variable dialog box, select the new category and use the up and down buttons to move it to the position where you want it to appear. Figure 7-35 Move up Figure 7-36 Move down If it is not already visible, choose View > View Properties

158 144 Chapter 7 from the menu to display the Properties pane: Figure 7-37 The Properties pane In the Column Text field in the Properties pane, type the text that you want to appear in each column for the new row. If you want the same text to appear in each column, simply type the text; for example: $. If you want different text to appear in each column, type the text to appear in each column, separated by a semi-colon; for example: ==========; -; -; - If there are more columns than text, the text will repeat from the beginning in the remaining columns. This means that if you want to repeat text for a set of columns, say in a nested table, you can type the text for the first set of columns and it will repeat for the remaining columns. For example, =====; will display as ===== ===== ===== if there are six columns. If there are more text strings than columns, the additional strings are ignored. Choose Save and Close to save your changes and return to the Design pane. Choose the Results pane to regenerate the table and display the results. Removing categories from a variable You may not want to include all of the categories in a variable when you create a table. For example, you may want to exclude a category that does not contain any responses, or you may want to exclude the data for a particular category from your analysis.

159 145 Using variables You can use various methods to prevent categories from appearing in tables. The method you use will depend on your exact requirements. The examples below show the results of using different methods to remove the 65+ years category from a table of age by gender: Figure 7-38 Basic table of age by gender Note: These examples are intended to show the results of applying different methods to the same table, rather than to give examples of real world tables. Deleting a category from a variable This method removes the category from the table, so that it is not displayed in the table row or column. The case data is not removed from the base. However, as the category no longer forms part of the table specification, values for deleted categories are not included in any totals or subtotals that you add to the table. You can delete a category either for all tables that use the variable, or for the currently selected table. Figure years category deleted In this example, the 65+ years category has been deleted from the variable. For more information, see the topic Deleting a category on p. 148.

160 146 Chapter 7 Filtering out a category This method restricts the cases that are included in a table. The values for the filtered-out category do not appear in the row or column for the category. They are also excluded from the base and from any calculations that use the base. If you have added totals or subtotals to the table, the category values are also excluded from these items. The category row or column is still displayed in the table, but the cells do not contain any data. For more information, see the topic Filtering YourResultsinChapter6onp. 92. Figure years category filtered out In this example, a filter has been added to the basic table to filter out the 65+ years category. For more information, see the topic Creating a Filter in Chapter 6 on p. 92. You can combine filtering and deleting to remove a category both from the case data (so that it does not appear in the base) and from appearing in the table. Figure years category filtered and deleted In this example, a filter has been added to the basic table to filter out the 65+ years category, and the category has also been deleted from the variable. Hiding a category This method prevents a category from being displayed in the table, without removing it from the variable or from the base. As the hidden category still exists in the table specification, values for the category are included in any totals and subtotals that you add to the table.

161 147 Using variables Figure years category hidden In this example, the 65+ years category has been hidden from the table. For more information, see the topic Hiding a category on p xcluding a category from the base This method removes the values for the category from the base and from any calculations that use the base, while still displaying the category values in the table. As the category still exists in the table specification, the values for excluded categories are included in any totals and subtotals that you add to the table. Figure years category excluded from base In this example, the 65+ years category has been excluded from the base. You can use a combination of the Hide and Include In Base properties to remove a category both from the base and from the table display. However, as it is still part of the table specification it still appears in any totals and subtotals that you add to the table.

162 148 Chapter 7 Figure years category hidden and excluded from base In this example, the 65+ years category has been hidden from the table and excluded from the base, by using the Hide and Include In Base properties. Hiding rows or columns You can also prevent rows or columns from being displayed in a table if the base counts are below a value that you specify. This does not remove the values contained in the hidden rows or columns from the base, or from any total or subtotals that you add to the table. Figure years category suppressed In this example, rows with base counts below 20 have been hidden (which has the effect of suppressing the 65+ years row). Although in this example the result is to hide a single category, this method applies to the whole table, not to individual categories. For more information, see the topic Hiding a Row or Column in Chapter 15 on p Deleting a category You can delete a category from a variable so that it does not appear in tables. Deletingacategory In the Variables pane, select the variable.

163 149 Using variables From the menu, choose: Variables > dit Variable This opens the dit Variable window and displays details of the variable. From the menu, choose dit > Delete Alternatively, press the Delete key or choose the Delete button: Figure 7-46 Delete button The category is removed from the list. Choose Save and Close from the toolbar. Hiding a category You can delete a category from a variable so that it does not appear in tables, but is still available in case you want to add it back in again at a later date. Hiding a category In the Variables pane, select the variable. From the menu, choose: Variables > dit Variable This opens the dit Variable window and displays details of the variable. From the menu, choose Categories > Hide Alternatively, choose the Hide button: Figure 7-47 Hide button Choose Save and Close from the toolbar. Creating new variables In addition to editing variables that already exist in the survey data file, you can create your own variables. This gives you the flexibility to make changes while still retaining the original variable (if you want to make changes to a variable that apply only to a single table, see also the dit Table Variable option described in diting variables). You can create new variables in a number of ways: Save an existing variable with a new name

164 150 Chapter 7 Copy an existing variable Create a new variable based on the current definition for the variable or combination of variables in either the side or the top of the table Merge two or more existing variables Create a new variable using your own definition. Saving a variable with a new name You can create a new variable by editing an existing one and saving it with a different name. This is useful when you want to define alternative ways of tabulating the same variable. You can copy numeric, categorical, text, date, or Boolean variables. Saving a variable with a new name Select the variable and edit it as required. For more information, see the topic diting variables on p From the menu, choose File > Save Variable As In the Save Variable As dialog, enter a name and description for the variable. nsure that the variable name conforms to the IBM SPSS Data Collection Survey Reporter Naming Conventions. Choose OK. Choose Save and Close from the toolbar to close the dit Variable dialog box. The dialog box closes and the variable appears in the Variables pane. Copying a variable You can create a new variable by copying an existing one. This is useful when you want to define alternative ways of tabulating the same variable, if you have previously saved the variable. You can copy numeric, categorical, text, date, or Boolean variables.

165 151 Using variables Copying a variable In the Variables pane, select the variable that you want to copy: Figure 7-48 Selecting a variable From the menu, choose Variables > Copy This displays the New Variable window. Because you are creating a new variable rather than editing an existing variable, the variable has an automatically generated name such as NewVar. The text Based on, followed by the name of the original variable, is displayed on the right of the window. Select the default name and change it to a meaningful name for your variable. It is generally a good idea to base the new variable s name on the name of the variable you are copying. For example, if the existing variable is called visits, you may want to call the new one visitsbanded,so that they will appear next to each other in the Variables pane when it is sorted in name order, and to help identify the content of the new variable. nsure that the variable name conforms to the IBM SPSS Data Collection Survey Reporter Naming Conventions. A default description is displayed in a text box beneath the name. You can edit this to give the new variable a meaningful description. dit the variable as required. Choose Save and Close from the toolbar. You can now use the new variable in your tables. Creating a variable from the side or top of a table You can create a new variable based on the definition of the side or top of a table. This is useful, for example, if you have set up a banner containing more than one variable on the top of a table, and you want to use it in other tables. Note: An alternative method of creating tables that have the same variables on top is to use the Multiple with Same Top option. For more information, see the topic Creating multiple tables with the same top variable in Chapter 4 on p. 60.

166 152 Chapter 7 Creating a variable from the side or top Use the Design tab to set up the top or side definition. Click inside the Top or Side area of the screen to select it. Figure 7-49 From the menu, choose Variables > New from Side/Top nter a name and description for the new variable, and choose OK. nsure that the variable name conforms to the IBM SPSS Data Collection Survey Reporter Naming Conventions. Merging variables You can merge two or more variables to form a new variable. This is useful when you want to create a total awareness variable or when you want two or more categorical variables to be treated as one variable in your tables. When merging categorical variables, the new variable will automatically have the same categories as the categorical variables you are merging. If the same category appears in more than one of the variables, it will appear only once in the new variable. When merging text variables, the new variable will contain the texts from the text variables you are merging, concatenated together. When merging numeric or date variables, the new variable will contain the sum of the values stored in the variables you are merging. When merging any variables, the variables that you select: must be of the same type (although they can be a mixture of single response and multiple response categorical variables) must be at the same level if you are using hierarchical data. The level of the variables you select defines the level of the new variable. For example, if you select variables in the Person loop, the new merged variable will also be at the Person level.

167 153 Using variables If any of the variables you are merging has been edited, the edits will not be copied to the new variable. For example, suppose you merge two categorical variables from which you have deleted one or two categories. The new variable will include the deleted categories. When you merge variables that contain any built-in special items, the new variable will not contain any of the built-in special items. You are most likely to see this when you are working with IBM SPSS Quanvert data, which typically contains built-in special items. For example, if you merge two Quanvert variables, either or both of which contain a built-in mean, the new variable will not contain a mean. Similarly, built-in bases are not copied to the new variable and IBM SPSS Data Collection Survey Reporter will therefore insert an autobase into the new variable. Merging variables In the Variables pane, use Shift+click or Ctrl+click to select the variables that you want to merge. From the menu, choose Variables > Merge This displays the New Variable window. Because you are creating a new variable rather than editing an existing variable, the variable has an automatically generated name such as NewVar. The text Based on, followed by the name of the original variable, is displayed on the right of the window. Select the default name and change it to a meaningful name for your variable. nsure that the variable name conforms to the Survey Reporter Naming Conventions. A default description is displayed in a text box beneath the name. You can edit this to give the new variable a meaningful description. Make any further edits to the variable using the features in the New Variable dialog box. Choose Save and Close from the toolbar. You can now use the new variable in your tables. Advanced variable definitions You can create a new variable and specify the variable definition from scratch, rather than by starting from one or more existing variables. Creating a new variable Place the cursor in the Variables pane by selecting the variable after which you want the new variable to appear. If you are using hierarchical data, the position you select before creating the variable defines the level of the variable. For example, if you place the cursor in the Person loop, the new variable will be at the Person level. From the menu, choose Variables > New Tip: You can also press Ctrl+M.

168 154 Chapter 7 The New Variable dialog box appears. Select the default name NewVar and change it to a meaningful name for your variable. nsure that the variable name conforms to the IBM SPSS Data Collection Survey Reporter Naming Conventions. A default description is displayed in a text box beneath the name. You can edit this to give the new variable a meaningful description. Select a variable type for the new variable from the drop-down list. Choose the Select button at the right of the Based on field. This displays the Create New Variable Based On dialog box, where you can enter the definition of the variable. Choose OK to close the dialog box and return to the New Variable dialog box. For categorical variables, indicate whether the variable is a single response or a multiple response variable by using the Number of Responses dialog box to specify how many responses can be recorded for a respondent. For more information, see the topic Setting the number of responses in avariableonp Make any further edits to the variable using the features in the New Variable dialog box. Choose Save and Close from the toolbar. You can now use the new variable in your tables. Creating a new variable: examples This topic shows you some examples of how to create new variables using the New Variable dialog box. Some of these examples can also be achieved by other methods, for example, using the Copy or Merge options. Copying an existing variable To make a copy of another variable, simply type the name of the variable you want to copy in the text box. For example, if you want the new variable to be a copy of the age variable, type: age into the New variable syntax text box. When making a copy of another variable, ensure that the new variable has the same data type as the variableyouarecopying(whenyouusethecopy option on the Variables menu, the new categorical variable will automatically have the same categories as the variable you are copying). Merging categorical variables To merge two or more categorical variables, enter the names of the variables you want to merge separatedbythe+ operator. For example, if you want to create a total awareness variable from variables called Favorite, Spontaneous, and Prompted, type: Favorite + Spontaneous + Prompted

169 155 Using variables into the New variable syntax text box. The new categorical variable will automatically have the same categories as the variables you are combining. If the same category appears in more than one of the variables, it will only appear once in the new variable. Numeric variables To create a new numeric variable and base it on a formula that uses one or more existing numeric variables, type the formula into the text box using the names of the existing variables. For example, in the Museum sample the visits and visits12 variables are both numeric. You could create a new numeric variable based on the following expression: visits12 / visits * 100 Boolean variables To create a new Boolean variable for use as a filter, enter the expression for the variable. For example, the following expression selects respondents who are male: Gender = {Male} Text variables Sometimes you may want to concatenate two or more text variables, but separate the text in the variables using a specific character. The following expression concatenates the name and address variables and separates the text with a colon and a space: name + ": " + address Deleting variables You can delete variables that you have created using IBM SPSS Data Collection Survey Reporter. This permanently deletes them from the table document (.mtd) file, so before deleting a variable, ensure that you will not require it at a later date. If you delete a variable that you have already added to a table, the variable is deleted from the Variables pane but remains on the table until you specifically delete it from that table. You can also delete variables that come from the survey data file. The variables are permanently deleted from the table document (.mtd) file. Note, however, that the variables are not deleted from the survey data file itself, so you can always return to the original variables by opening the file again using a new table document. If you edited the variable after opening the file, however, only the original variable will be available, not your edits. An alternative method of removing a variable is to hide the variable so that it does not appear in the Variables pane. For more information, see the topic Hiding Variables in Chapter 3 on p. 47. Deleting a variable Select the variable in the Variables pane, and press the right mouse button. From the context menu, choose Delete. At the prompt, choose Yes.

170 156 Chapter 7 Deleting changes to variables You can delete the changes you have made to a variable. For categorical variables, this reinstates the categories and built-in items defined for the variable in the metadata. For all other variable types, this clears the axis expression. If the variable has an axis expression defined in the metadata, this does not restore it. Deleting changes to a variable Double-click the variable in the Variables pane to open the dit Variable dialog box. From the dit Variable menu, menu, choose File > Clear dit Choose Save and Close to save the changes. dit Variable dialog box Use the dit Variable dialog box to specify the content of variables when they appear in your tables. To open the dit Variable dialog box, double-click on a variable name in the Variables pane or select a variable in the Variables pane and choose Variables > dit Variable from the menu. Fields on the dit Variable dialog box The dit Variable menu. For more information, see the topic The IBM SPSS Data Collection Survey Reporter Menus in Chapter 3 on p. 32. The dit Variable toolbar. For more information, see the topic The IBM SPSS Data Collection Survey Reporter Toolbar Buttons in Chapter 3 on p. 35. Name. You cannot change the variable name in the dit Variable dialog box. To rename a variable, use the Variables pane. For more information, see the topic Renaming Variables in Chapter 3 on p. 45. Description. The default description is the variable s description (label) or the text of the question on which it is based. You can change the variable description if required. The description appears in the Results tab, if you have chosen to display variable descriptions. Any changes you make to the description will be applied to any existing tables that include the variable next time you generate them. Data type. Displays the variable s type. Category list. The main section of the dialog box displays a list of the categories in the variable. This list also includes other items that are part of the variable, for example, means, totals, or other items that you create.

171 157 Using variables Properties pane. The Properties pane is an advanced feature that you can use to view and edit the properties for categories and other items in a variable. For more information, see the topic dit Variable dialog box: Properties pane on p Script pane. The Script pane is an advanced feature that you can use to display and edit the syntax for a variable. For more information, see the topic dit Variable dialog box: Script pane on p The changes you make in this dialog box define how the variable appears when you add it to a table. Any changes you make here are not shown in the tooltips in the Variable List and are not available for defining filter conditions. For example, suppose you use the Insert Bands dialog box to categorize the values in a numeric variable into two bands called High and Low. Whenyou subsequently create a filter based on this numeric variable, the High and Low bands will not appear in the Filter tab and you will not be able to specify them in an advanced filter expression. For more information, see the topic Filter Conditions in Chapter 6 on p Generally any changes you make in the dit Variable dialog box will affect all tables that include the variable, although the changes will not be visible in existing tables until you repopulate them. However, changes will not affect any tables where you have used the dit Table Variable dialog box to define how the variable is to appear in those specific tables. dit Variable dialog box: Properties pane Figure 7-50 Properties pane The Properties pane is an advanced feature that you can use to view and edit the properties for categories and other items in a variable. For example, you can exclude a category from the base for the variable, change the variable used as the basis for the calculation of means and other special items, or change the weighting applied to a category. You can change more frequently used properties (for example, descriptions or factors) using the menu options and toolbar buttons in the dit Variable dialog box. To display the Properties pane, choose View > View Properties

172 158 Chapter 7 from the dit Variable dialog box menu, or choose the View Properties button: Figure 7-51 View Properties button Fields on the Properties pane The table below displays the complete list of category properties, together with the name of the corresponding property or properties in the Table Object Model. If you edit the variable syntax directly using the Script pane, you must use the Table Object Model property name. Not all properties are available for all category types. Property Purpose Property Name in Table Object Model Calculation properties Cut-off value Based on Calculation scope For a percentile, set the value below which a certain percentage of the cases fall. For mean, sample variance, standard error, and standard deviation, define whether to base the item based on factors or a numeric variable, and if so, which one. For minimum, maximum, median, mode, percentile, numeric or sum items, use this option to select the numeric variable on which a minimum or maximum is based. If you use factors to calculate a mean, standard deviation, standard error or sample variance, you can specify whether you want the mean to be calculated for all the categories, or for just those categories preceding the mean in the table. The default calculation scope is all categories when you create the mean in IBM SPSS Data Collection Survey Reporter. The default is preceding categories when the mean exists in the metadata. This is for compatibility with IBM SPSS Quanvert data sources. By default non-category elements, that can be filtered by an expression, are filteredbythe net when added to a net. For example, the mean element in the net only includes the elements in the net. If the CalculationScope property of net element is set with csalllements, the factor mean includes all CutOffValue AnalysisVariable CalculationScope

173 159 Using variables Property Purpose Property Name in Table Object Model xpression Factor Include in base elements, including elements in top and elements within nets. The default CalculationScope property for a net element is csprecedinglements. For means, and other special items that can be restricted by an expression, enter an expression using the appropriate syntax; for example, gender={male}. For more information, see the topic lement Syntax in Chapter 19 on p For user-defined or derived categories, click the... button to enter an expression in the dit User-Defined Category or dit Derived Category dialogs. nter a factor for a category, including combined categories and nets. A factor is a constant numerical value that can be assigned to a category in a categorical variable for use in statistical calculations. Factors areusedwhenyouwantto base a summary statistic on the categories in a variable, rather than on a numeric variable. This is because statistics can be calculated on numeric data only and categories are not true numeric values. (Although the IBM SPSS Data Collection Data Model represents the responses to categorical questions as numeric values, these are in fact identifiers or codes and are not suitable for statistical analysis.) By default, all categories in the original variable are included in the variable s base. You can exclude a category from the base by selecting No for this option. xpression Factor IncludeInBase

174 160 Chapter 7 Property Purpose Property Name in Table Object Model Increment count by value in By default, cell counts are incremented by one for each case that meets the required conditions for the cell. Use this option to specify a numeric variable, and force the count value to be incremented by the value for the numeric variable for that case instead of by one. Cell items that use an analysis variable, for example, Sum, are incremented by the value of the specified analysis variable. Use this option to specify a numeric variable, and force the value to be incremented by the product of the analysis variable value and the value of the numeric variable. Note: Using a multiplier at a parallel level is not supported. A valid multiplier for a variable should meet the following conditions: A numeric variable. At the same ascendant level as the variable. An example for the variable person[..].trip[..].purpose: Same level multiplier (valid):person[5].trip[..].transportmodes Ascendant level multiplier (valid): person[..].age, numpersons Parallel level (invalid): vehicle[..].mileage Multiplier Override table weight using Display properties Decimal places Description By default, categories use the weight applied to the table using the Table Properties dialog box. Use these options to set a different weight,ornoweightatall,fora specific category. You can specify the number of decimal places for statistical variables such as mean or standard deviation, and for other items such as totals and unweighted bases. The number of decimals you enter here overrides the value you enter for cell contents using the Table Properties dialog box. This is the text that is displayed in the row or column header when the category is on the side or top of a table. IsUnWeighted Weight Decimals Label

175 161 Using variables Property Purpose Property Name in Table Object Model Hide options Keep fixed when sorting Miscellaneous (read-only) Name Specification Type By default, categories and other items are automatically displayed in the table when you add them. Select from these options to hide the category so that it never appears on a table, or to hide it onlywhenitoccursonthetopor on the side of a table. Specifies that an element s position in the row or column is fixed when the table is sorted. You cannot change the category s name in this pane. You can change the name of a category by editing the variable syntax using the Script pane. This is the full syntax for the category. The specification is blank for categories that are built into the variable. This shows the category or item type. These correspond to the items that you can create in a variable, such as user-defined categories, means, totals and so on. For more information, see the topic Insert Categories dialog box on p IsHidden IsHiddenWhenColumn IsHiddenWhenRow IsFixed Name Specification Type dit Variable dialog box: Script pane Figure 7-52 Script pane

176 162 Chapter 7 The Script pane is an advanced feature that you can use to display the syntax for a variable. The syntax is automatically updated as you change the contents of the variable using the Properties tab or the menu options and toolbar buttons in the dit Variable window. You can also edit the syntax directly by typing into the Script pane and choosing the Apply button. To display the Script pane, choose View > View Script from the dit Variable dialog box menu, or choose the View Script button: Figure 7-53 View Script button Save Variable As Use the Save Variable As dialog box to save a variable based on an existing variable (leaving the original variable unchanged), or based on the combination of variables on the side or top of the table. This dialog box appears when you select a variable in the Variables pane and choose Variables > dit Variable from the menu, then choose Save As from the menu or toolbar. This dialog box also appears when you select the top or side of a table and choose Variables > New from Side or Top Fields on the Save Variable As dialog box Name. nteranewnameforthevariable.itisgenerallyagoodideatobasethenewvariable s name on the name of the variable you are copying. For example, if the existing variable is called visits, you may want to call the new one visitsbanded, so that they will appear next to each other in the Variables pane when it is sorted in name order, and to help identify the content of the new variable. nsure that the variable name conforms to the IBM SPSS Data Collection Survey Reporter Naming Conventions. Description. nter a meaningful description for the new variable. Insert Categories dialog box Use the Insert Categories dialog box to add new categories or other items such as means, totals, to avariable. To open the Insert Categories dialog box, first open the dit Variable or New Variable dialog box. From the menu, choose Categories > Insert Categories

177 163 Using variables Figure 7-54 The Insert Categories dialog box Fields on the Insert Categories dialog box Available items. This lists all of the possible types of category and other items that you can add to a variable. The following items are available, in addition to any categories and built-in special items in the variable that have been removed from the variable s definition. To add an item, select it and click the >> button. Item User-defined category Base Purpose This creates a new category based on a custom expression. After inserting the item, you must define the expression on which the new category is to be based. For more information, see the topic Creating a category based on another variable on p Shows the total number of cases in the variable. Generally, the base includes every case for which the value stored in the variable is not Null. IBM SPSS Data Collection Survey Reporter automatically adds a base to any variable that does not have one, which means that normally you do not need insert a base. For more information, see the topic Base Rows and Columns in Chapter 8 on p. 182.

178 164 Chapter 7 Item Unweighted base Mean Minimum Maximum Standard deviation Standard error Purpose Shows the total number of cases in the variable before any weighting has been applied. In an unweighted table, an unweighted base shows the same values as the counts in the base. Only one value is ever shown for an unweighted base, even when multiple types of cell contents have been requested. The value that is shown is the unweighted base count, regardless what type of cell contents have been requested for the table. By default Survey Reporter automatically adds an unweighted base as the first item in the top and side of a weighted table. For more information, see the topic Showing the Unweighted Base in Weighted Tables in Chapter 10 on p Shows the mean value, which is a measure of central tendency. It is the arithmetic average the sum divided by the number of cases. You can create a mean to show the mean value of a specified numeric variable. Alternatively, you can create a mean to show the mean value of the factors associated with the category and expression items in the axis. For more information, see the topic Adding summary statistics to a categorical variable on p Shows the minimum value of a numeric variable. Shows the maximum value of a numeric variable. Shows a measure of dispersion around the mean. In a normal distribution, 68% of cases fall within one standard deviation of the mean and 95% of cases fall within two standard deviations. For example, if the mean age is 45 with a standard deviation of 10, then 95% of the cases would be between 25 and 65 in a normal distribution. You can show the standard deviation for a specified numeric variable. Alternatively, you can show the standard deviation for the factors associated with the category and expression items in the axis. Shows a measure of how much the value of the mean may vary from sample to sample taken from the same distribution. The standard error of the sample mean can be used to estimate a mean value for the population as a whole. In a normal distribution, 95% of the values of the mean should lie in the range of plus or minus two times the standard error from the mean. Additionally, the standard error can be used to roughly compare the observed mean to a hypothesized value of another mean (that is, you can conclude that the two values are different if there is no overlap in the values of the means plus or minus two times the standard error). You can show the standard error for a specified numeric variable. Alternatively, you can show the standard error for the factors associated with the category and expression items in the axis.

179 165 Using variables Item Sample variance Subtotal Total Subheading Column text Paired preference Derived category Numeric Sum ffective base Net difference Median Percentile Mode Purpose Shows a measure of dispersion around the mean, equal to the sum of squared deviations from the mean divided by one less than the number of cases. The variance is measured in units that are the square of those of the variable itself. You can show the sample variance for a specified numeric variable. Alternatively, you can show the sample variance for the factors associated with the category and expression items in the axis. The sum of the counts between the most recent base, total, or subtotal, whichever is the most recent, and the next base, total, or subtotal, or the end of the axis, whichever occurs first. A subtotal works in this way regardless of its position in the axis. The sum of the counts between the most recent base or total, whichever is the most recent, and the next total or base, or the end of the axis, whichever occurs first. A total works in this way regardless of its position in the axis. A text-only item that can be used to form a subheading. A text-only item that can be used to form a subheading. When the variable is on the side of the table, the item forms a text-only row. For more information, see the topic Adding text rows to tables on p Shows the results of a paired preference test. For more information, see the topic Adding a Paired Preference Test or a Net Difference Test in Chapter 9 on p Shows a derived category calculated from other categories within the variable using an arithmetic expression. For more information, see the topic Creating a category based on other categories on p This creates a new item based on a numeric variable. You can use this to create a summary variable that references a number of other variables. Shows the sum or total of the values in a specified numeric variable. Displays the effective base. This is calculated by dividing the squared sum of weights for all of the respondents in the table by the sum of the squared weights. Displays the result of a net difference test. Displays the median for a numeric variable. Displays a percentile for a numeric variable. Displays the mode for a numeric variable.

180 166 Chapter 7 Item T-Value T-Probability Purpose Determines whether the mean of a numeric variable is significantly different from zero or some other specified value. For more information, see the topic T-test Test in Chapter 9 on p Determines whether or not there is a relationship between the data being tested. Refer to T-test Test and pvaluesfor more information. For more advanced information about the items you can enter, see lement Syntax. When calculating the values for mean, standard deviation, standard error, sample variance, minimum, and maximum items, Survey Reporter uses the same formulae used for the cell contents. For more information, see the topic Formulae for Cell Contents in Chapter 19 on p Items to insert. Lists the items in the order in which they will be displayed. To remove an item, select it and click the >> button. Move up/move down. Select an item in the Items to insert list and choose the Move up or Move down button to change the order in which the categories will be inserted into the variable. Description. Displays an automatically generated description for the category, which you can change to show a meaningful description. Category descriptions appear in your tables and charts if you have chosen to display them instead of category names. For more information, see the topic Changing the description for a category on p Decimals. Displays the default number of decimal places for the type of item selected. dit Item This button is available when you select a category that supports expressions. Choose this button to open the dit User-Defined Item dialog box or dit Derived Category dialog box where you can enter a definition for the category. dit User-Defined Item dialog box You can usethedituser-defined Item dialog box to define and modify the expression for a user defined item. The top part of the dialog box displays the name and label for the category. The dit User-Defined Item dialog box is available from the dit Item button in the Insert Categories dialog box.

181 167 Using variables Figure 7-55 dit User-Defined Category dialog box On the left side of the dialog box is a list of the variables in the survey data file. For more information, see the topic The Variables Folders Pane in Chapter 3 on p. 43. The right side of the pane varies according to the type of variable you have selected. Use this area to define the condition for the category. For more information, see the topic Filter Conditions in Chapter 6 on p When you add multiple conditions, the conditions are displayed on separate lines. You can select a line to change or remove it. For more information, see the topic Adding Multiple Conditions toafilterinchapter6onp If you are using the hierarchical view of the data, the expression s level is controlled by the level of the variable to which the item belongs. For more information, see the topic Filtering Hierarchical Data in Chapter 11 on p dit Derived Category dialog box You can use the dit Derived Category dialog box to enter the calculation for a category that derives its value from that of other categories in the variable. To open the dit Derived Category dialog box, first create a derived category using the Insert Categories dialog box, then choose the dit Item button.

182 168 Chapter 7 Figure 7-56 The dit Derived Category dialog box showing the categories in the age variable Fields on the dit Derived Category dialog box Variable. The left of the dialog box displays the name of the variable, and lists all the categories in the variable. Drag categories from this list and drop them into the text box on the right of the dialog box to add them to the expression for the derived category. You can also add to the expression by typing directly into the text box, or by copying and pasting all or part of the expression from another application such as Notepad. Derived categories use an arithmetic expression based on the values of other categories in the table. This differs from using an expression in a user-defined category, which uses a logical expression that tests the case data to determine whether a respondent is included in the count. Insert Bands dialog box Use the Insert Bands dialog box to create one or more bands for a numeric or date variable. To open the Insert Bands dialog box, open the dit Variable or dit Table Variable or New Variable dialog box for a numeric variable. To open this dialog directly from the dit Variable dialog box, choose Categories > Insert Bands

183 169 Using variables or choose the Insert Bands button on the toolbar: Figure 7-57 Insert Bands button Figure 7-58 Insert Bands dialog box Fields in the Insert Bands dialog box Get values from data. Choose this button to base your bands on the range of values collected from respondents. For example, in the Museum questionnaire, questions such as Number of Previous Visits question allow any response between 1 and 99, but if no respondent gave an answer of over 20 it makes sense to band on the respondent data rather than the whole of the valid range. The minimum and maximum values from the survey data are added to the From and To fields. From. nter the lowest value of the first band you want to add. To. nter the highest value of the final band you want to add. Number of bands. nter the number of bands you want to create. Decimal places. nter the number of decimal places you want to display for the bands. Add Factors dialog box Use the Add Factors dialog box to insert factors for all the categories or selected categories in avariable. To open the Add Factors dialog box, first open the dit Variable, dit Table Variable, or New Variable dialog box. Optionally, highlight the categories to which you want to add factors. From the menu, choose Categories > Add Factors

184 170 Chapter 7 Figure 7-59 Add Factors dialog box Fields in the Add Factors dialog box Categories to assign factors to. Choose whether to add factors to: All: all the categories listed for the variable. If you choose this option, you can also choose whether to exclude special categories such as No Answer or Don t Know. Selected: only categories that you have highlighted in the dit Variable dialog box. Factors to assign. Choose from: Standard: a number of standard sequences. The factors are applied to the categories in the order in which they appear in the dit Variable dialog box. Custom: your own custom sequence. To assign custom factors, enter a value for the first factor in the Start Value field and a value by which to increase the factor in each subsequent category in the Increment value field. For example, you may want the first category to have a factor of 10, and subsequent factors to increase by 10 for each category. Optionally, you can decrement the categories rather than increment them, by choosing the Decrement factors option. Note: If you add, delete, or reorder the categories in a variable, the factors are not updated automatically. You can use this dialog box again to apply factors to a variable that already has factors for some or all of the categories. Note that in this case the existing factors will be overwritten. Setting the number of responses in a variable Use the Number of Responses dialog box to specify the maximum number of responses that are allowed for a respondent in the variable. When you create new variables, this enables you to specify whether a variable is a single response or a multiple response variable. When you edit

185 171 Using variables existing variables, you must specify the maximum number of responses if you add expressions or bands to a variable, if this results in the variable having a larger number of possible responses than originally specified for it. For example, suppose that a survey contains a question to which respondents can choose one of the following responses: Very Satisfied, Fairly Satisfied, Neither Satisfied nor Dissatisfied, Fairly Dissatisfied, and Very Dissatisfied. As respondents can select only one of these answers, the variable is stored as a single response variable, with a maximum response value of 1. You may decide to edit this variable to add a Top two box called Satisfied Customers that combines the Very Satisfied and Fairly Satisfied responses using the Combine and Keep option (because you also want to see the individual responses). As a result, the variable is no longer a single response variable because the same respondent can be recorded as having selected the top two box and also the Very Satisfied or the Fairly Satisfied response. Because of this, you must indicate that the maximum number of responses is now 2, not 1, so that IBM SPSS Data Collection Survey Reporter is able to carry out the correct calculations on the data. It is also necessary so that if you export the data, the output format is able to allocate space to store the additional response values. When should you change the maximum number of responses? Change the maximum number of responses for a variable if: you create a new variable, and you want to tell Survey Reporter whether it is a single response or a multiple response variable. For a single response variable, enter 1, for a multiple response variable, enter the maximum number of responses that can be selected for the variable by any respondent. you use the Combine and Keep option to create new categories while retaining the existing ones. you add a user-defined category to a single response variable, and the resulting category may be selected for any respondent in addition to an existing category. You also need to change this setting for numeric or text variables if you have converted them to categorical variables using bands or user-defined categories, if the categories or bands overlap. To display the Number of Responses dialog box, first edit the variable or create a new one, using the dit Variable, dit Table Variable, or New Variable dialog box. From the menu, choose Categories > Number of Responses

186 172 Chapter 7 Figure 7-60 Number of Responses dialog box nter a value in the Maximum number of responses for this variable field. This must be greater than or equal to the maximum number of responses that can be selected per respondent. dit Table Variable dialog box Use the dit Table Variable dialog box to specify the content of variables in the current table. If you want to make changes that will be stored in the variable for future tables, use the dit Variable dialog box, which you open using the dit option on the Variables menu. To open the dit Table Variable dialog box, select a variable that you have added to the Design pane, and choose Variables > dit Table Variable from the menu. Fields on the dit Table Variable dialog box The dit Variable menu. For more information, see the topic The IBM SPSS Data Collection Survey Reporter Menus in Chapter 3 on p. 32. The dit Variable toolbar. For more information, see the topic The IBM SPSS Data Collection Survey Reporter Toolbar Buttons in Chapter 3 on p. 35. Name. You cannot change the variable name in the dit Table Variable dialog box. To rename a variable, use the Variables pane. For more information, see the topic Renaming Variables in Chapter 3 on p. 45. Description. The default description is the variable s description (label) or the text of the question on which it is based. You can change the variable description if required. The description appears in the Results tab, if you have chosen to display variable descriptions. Data type. Displays the variable s type.

187 173 Using variables Category list. The main section of the dialog box displays a list of the categories in the variable. This list also includes other items that are part of the variable, for example, means, totals, or other items that you create. Properties pane. The Properties pane is an advanced feature that you can use to view and edit the properties for categories and other items in a variable. For more information, see the topic dit Variable dialog box: Properties pane on p Script Pane. The Script pane is an advanced feature that you can use to display and edit the syntax for a variable. For more information, see the topic dit Variable dialog box: Script pane on p You cannot edit loops and grids in this dialog box. However, provided you are using the hierarchical view, you can edit their descriptions in the dit Variable dialog box. This dialog box changes how the variable will appear in the current table only. If you subsequently make any changes to the variable in the dit Variable dialog box, those changes will not be applied to this table. (However, if you change the variable s description in the dit Variable dialog box, the changed description will be applied to this table next time you populate it.) New Variable dialog box The New Variable dialog box is an advanced feature that you can use to create a new variable. To open the New Variable dialog box, choose Variables > New from the menu, or press Ctrl+M. Fields on the New Variable Dialog Box The dit Variable menu. For more information, see the topic The IBM SPSS Data Collection Survey Reporter Menus in Chapter 3 on p. 32. The dit Variable toolbar. For more information, see the topic The IBM SPSS Data Collection Survey Reporter Toolbar Buttons in Chapter 3 on p. 35. Name. IBM SPSS Data Collection Survey Reporter generates a name for the new variable. You can change this to a more meaningful name. nsure that the variable name conforms to the Survey Reporter Naming Conventions. Description. nter a description for the variable as you want it to appear on your tables. Data type. Defines the new variable s type. When you are creating a copy of a variable, you must select the same type as the variable you are copying. The options are: Boolean Categorical Date

188 174 Chapter 7 Numeric (long) Numeric (double) Text For more information, see the topic Variable type overview on p Based On. Use this field to type in the syntax that defines the variable; for example, Favorite + spontaneous + prompted. This is useful if you are familiar with the syntax. Alternatively, define the variable using the dialog box available from the Select button. Select. Choose this button to display the Create New Variable Based On dialog box, whereyou can enter your own formula for the variable. Category list. The main section of the dialog box displays a list of the categories in the variable. This list also includes other items that are part of the variable, for example, means, totals, or other items that you create. Properties pane. The Properties pane is an advanced feature that you can use to view and edit the properties for categories and other items in a variable. For more information, see the topic dit Variable dialog box: Properties pane on p Script Pane. The Script pane is an advanced feature that you can use to display and edit the syntax for a variable. For more information, see the topic dit Variable dialog box: Script pane on p Note: You can also create a new variable by copying or merging existing variables, or saving changes to an existing variable as a new variable. For more information, see the topic Creating new variables on p Create New Variable Based On dialog box The Create New Variable Based On dialog box is an advanced feature that you can use to define the formula for a new variable. You enter the formula in the form of an expression. This expression also defines the base for the new variable when you use it in a table. For example, if you definetheexpressionasthenameofanothervariable,thenewvariablehasthesamebase as the other variable. If you leave the definition blank, IBM SPSS Data Collection Survey Reporter automatically uses an expression of {}, which means that all respondents are included in the base for the variable. To open the Create New Variable Based On dialog box, choose the Select button in the top right corner of the New Variable dialog box.

189 175 Using variables Figure 7-61 CreateNewVariableBasedOndialogbox Fields on the Create New Variable Based On dialog box xisting variables. The left of the dialog box displays all the variables in the current table document (.mtd) file. Double-click a variable from this list or select the variable and choose the >> button to add it to the expression for the new variable. New variable syntax. Usethisareatodefine the formula for the new variable. You can add variables by dragging and dropping from the xisting variables list, or you can type in the variable names. You can use any expression that is supported by the IBM SPSS Data Collection Data Model, including the functions in the IBM SPSS Data Collection Function Library. See the Function List for details of the functions available. See also the xpression valuation and IBM SPSS Data Collection Function Library topics in the IBM SPSS Data Collection Scripting section of the IBM SPSS Data Collection Developer Library for further information. How you specify variables in the expression depends on whether you are using the hierarchical or flat view of the data: When using the flat view, you cannot use any lower level variables or slices of variables. When using the hierarchical view, the level of the new variable and the expression is defined by the position of the new variable in the Variable List. Specify the names relative to the level of the new variable. (However, the names of variables inside a block should generally be preceded by the block name followed by a period (.). For example, to specify the Serial variable inside the Respondent block, specify the name as Respondent.Serial.) If you include in the expression any variables from other levels, you need to up-lev or down-lev them to the

190 176 Chapter 7 level of the new variable. For more information, see the topic Filtering Hierarchical Data in Chapter 11 on p Simple categorization Use the Simple Categorization dialog box to perform simple, non-linguistic categorization of variables by converting Text, Date or Numeric variables, which cannot be directly used in table tabulation, to Categorical variables. This allows data to be analyzed for reporting purposes. To open the Simple Categorization dialog box, select the appropriate variables and choose: Variables > Categorize > Simple... from the menu. The Simple Categorization Filter dialog box displays, allowing you to select which variables will be categorized: Figure 7-62 Simple Categorization Filter dialog Box Categorize all text variables. This is the default setting. When selected, all text, date and numeric variables are selected for categorization, regardless of which variables are currently selected. Categorize selected variables. When selected, only selected variables are categorized. Variables that are not text, date, or numeric are automatically filtered out Categorize all (text/date/numeric) variables. When selected, all text variables are selected for categorization, regardless of which variables are currently selected. Update existing variables. When selected, the Simple Categorization dialog box opens and lists all existing, categorized variables. Create new variables. When selected, the Simple Categorization dialog box opens with no defined categorized variables. You are required to create new variables. After selecting the appropriate categorization filter, and clicking OK, the Simple Categorization dialog box displays.

191 177 Using variables Fields on the Simple Categorization dialog box Selected variables. Displays the name of original variables coupled with the new variable names, such as OldVarName > NewVarName. By default the first variable in the list is selected and the name of its generated variable is shown in the New variable name field. If the new variable name is already in use, you are warned that the existing variable will be overwritten. The list supports multiple selections using CTRL + left click. When multiple variables are selected: The New variable name field is not available. The Category description format field is available. The full value, Maximum number of categories, andgenerate the Other category for any uncategorized data options are not available when more than one variable type is selected. The Custom categorization expression field is not available. New variable name. Displays the derived variable name for the selected variable. You can enter an appropriate variable name, or choose to accept the default name. This option is only enabled when you select Create new variables on the Simple Categorization Filter dialog box. Category description format (optional). Allows you to format the coded category description, where {Value} is the placeholder for the coded category. For example, if we typed in This is text before - <b>{value}</b> - and this is text after then each coded category description would follow this format. For example: Maximum number of categories. When selected, this user defined setting limits the number of categories generated for each variable. Generate the Other category for any other uncategorized data. When selected, an Other directory is created to include any data not included in the generated categories. This option is not limited by the value defined for Maximum number of categories. Treat empty values as. The following option are enabled by default. Not asked (NULL). When selected, empty and null values are ignored from base. User-missing category. When selected, a category is created for empty and null values, allowing users to set a category label. Categorization based on. The full value. When selected, each unique, full value of case data will be a category. This is the default setting.

192 178 Chapter 7 The first characters. When selected, the user-defined number of characters from the left side of each text value are trimmed, and each unique substring becomes a category. The last characters. When selected, the user-defined number of characters from the right side of each text value are trimmed, and each unique substring becomes a category. Ignore case. When selected, data case is not considered. For example, the two data entries ABC and abc become one category. This option is enabled by default. Remove leading and trailing spaces. When selected, leading and trailing spaces are removed from text values. This option is enabled by default. Custom categorization expression. This field allows advanced users to manually edit the variable expression. This field is not available when multiple variables are selected. More. ClicktodisplaytheadvancedCategorization based on options. Less. Click to hide the advanced Categorization based on options. Reset. Click to reset all variables in the Selected variables list back to their default settings. Preview. Click to preview the generated categorical variables, one-by-one, via the IBM SPSS Data Collection Survey Reporter preview dialog. Click OK after you are satisfied with categorization settings. The new categorical variables are created and displayed in the variable list based on the defined New variable name. Derived variable creation for database questions Automatically generating derived variables for database questions Derived variables are typically used in cases where database questions do not apply to specific operations. For simple and multiple database questions, derived variables are created on the help fields collection with the default name DBCodes. For database array questions, derived variable are created on the Array.Fields collection with the default name DBCodes.

193 179 Using variables Derived questions are automatically generated for database questions if the database questions do not already have any derived variables (otherwise the last derived variables are used). Derived variables are used, instead of the selected database questions, in the following situations: Adding to a new table/profile. Drag and drop the appropriate database questions from the Variable Folders pane to the appropriate Add buttons on the Design tab. You can also add the selected database questions to the table/profile by right-clicking the database questions and selecting the appropriate Add options (To Top or To Side for example). Adding to a filter. Drag and drop the selected database questions from the Variable Folders pane to the Add buttononthefilter tab. You can also add the selected database questions to the filter by right-clicking the database questions and selecting the Add > To Filter option. Variable Preview. Right-click the appropriate database questions on the Variable Folders pane and select the Generate Variable Preview option. You can also select the Generate Variable Preview option from the Variables menu. diting a user-defined item. Drag and drop the appropriate database questions from the Variable Folders pane to the appropriate Add buttons on the Design tab. You can also add the selected database questions by right-clicking the database questions and selecting the appropriate Add options (To Top or To Side for example). Manually generating derived variables for database questions Right-click the appropriate database questions from the Variable Folders pane and select the Categorize Database Variable... option. You can also select the Categorize > Database... option from the Variables menu. The Database Categorization dialog displays, providing option for creating derived categorical variables. For more information, see the topic Database categorization on p Database categorization Use the Database Categorization dialog box to create derived categorical variables (as database variables cannot be used directly in table definitions, filters, and tabulation). To open the Database Categorization dialog box, select the appropriate variables and choose: Variables > Categorize > Database... from the menu.

194 180 Chapter 7 The Database Categorization Filter dialog box displays, allowing you to select which database variables to categorize and define how they will be categorized: Figure 7-63 Database Categorization Filter dialog Categorize Provides options for selecting how derived variables are created for database variables. Categorize all database variables. When selected, derived variables are created for all database variables. Categorize selected database variables. When selected, derived variables are only created for selected database variables. This is the default setting. Variable creation Provides options for defining variable creation behavior. Update existing variables. When selected, new categorical variables are created for database variables that have no derived variables. All database variables that have derived variables are also updated. This is the default setting. Create new variables. When selected, new categorical variables are created for database variables regardless of whether or not the database variables already have derived variables. After selecting the appropriate options, click OK to display the Database Categorization dialog box.

195 181 Using variables Figure 7-64 Database Categorization dialog Fields on the Database Categorization dialog box Selected variables. Lists the database variables currently selected for categorization. Selecting a variable from the list will display that variable s defined settings under the Options section. New variable name. Displays the new derived categorical variable name for the selected database variable. You cannot specify a new name if you selected the Update existing variables option on the. Maximum number of categories. When selected, this user defined setting limits the number of categories generated for each variable. Generate the Other category for any other uncategorized data. When selected, an Other directory is created to include any data not included in the generated categories. This option is not limited by the value defined for Maximum number of categories. Treat empty values as. The following option are enabled by default. Not asked (NULL). When selected, empty and null values are ignored from base. User-missing category. When selected, a category is created for empty and null values, allowing users to set a category label. After defining the appropriate settings for each database variable, clicking OK will create the necessary derived variables.

196 Base Rows and Columns Chapter 8 A base row or column typically shows the total number of cases in a variable and is used in the calculation of percentages and statistical tests. IBM SPSS Data Collection Survey Reporter automatically adds a base to the start of every variable that does not already have one. Automatically inserted bases are sometimes called autobases. A variable must always contain at least one base. If you remove the base from a variable, Survey Reporter will automatically add an autobase to the variable in the table. However, you can hide thebaseinthetable. Calculation of the Base When calculating the base, IBM SPSS Data Collection Survey Reporter includes every case for which the case data stored in the variable is not Null. A value of Null is a special marker that indicates that the value is not known and generally indicates that the question on which the variable is based was not asked. A value of Null is different from an empty or zero value. When a respondent is asked a categorical or open-ended question but for some reason does not answer, the case data generally stores an empty categorical value ({}) or an empty string ( ) respectively (although some questions have one or more special categories to indicate that the respondent did not provide an answer). Consequently, for categorical and text data, it is possible to distinguish between a question that was asked but not answered and one that was not asked at all. However, in numeric data it is not possible to distinguish questions that were asked but not answered from those that were not asked at all, because the IBM SPSS Data Collection Data Model currently stores a Null value for both. Inasimplesurveywhereacasecorrespondstoarespondent, the base generally includes every respondent who was asked the question on which the variable is based, regardless of whether he or she actually answered it or not. When you use a subset of the categories in a variable on the side or top of the table, the base is the same as when you select all of the categories. To illustrate this, we will use the signs variable in the Museum XML survey data file to create an unfiltered one-dimensional table: Figure 8-1 Unfiltered one-dimensional table based on the Signs variable Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

197 183 Base Rows and Columns Notice that the base is 298, which is the sum of the counts in the three categories. This is a single response variable and all of the respondents who were asked the question answered it. Note that if any of the respondents had not answered the question, they would be included in the base too. Now let s include only the first two categories: Figure 8-2 Unfiltered one-dimensional table based on the Signs variable but including only the first two categories Notice that the base is still 298, but it no longer represents the sum of the counts in the categories on the table. This is because the base represents the number of respondents who were asked the question and is not based on the counts in the categories that have been selected for inclusion on thetable.ifyouwantthebasetoreflect only the respondents who selected the categories that are shown on the table, you would need to use a filter. For example, here is the table after adding a filter to exclude respondents who did not choose either of the two categories that are shown: Figure 8-3 Filtered one-dimensional table based on the Signs variable but including only the first two categories Notice that the base is now 271, which is the sum of the counts in the two categories that are shown on the table. Now suppose we want to add a mean element based on the visits numeric variable to the axis in the unfiltered table: Figure 8-4 One-dimensional table based on the Signs variable including only the first two categories and a special mean element based on the Visits numeric variable The visits variable is a numeric variable, which means that it stores a Null value for respondents who were not asked or did not answer the question on which it is based. In the Museum sample, the visits variable stores a Null value for some of the respondents who are included in this table. When Survey Reporter calculates the base used by the mean value calculation, it includes only respondents who are included in the table base and for whom the numeric variable does not store a Null value. The following table lists some hypothetical responses and shows whether the case is included in thebasefortheaxisandthebaseforthemean. Case Value in Signs Variable Value in Visits Variable Included in Axis Base in Unfiltered Table 1 {Yes} 4 Yes Yes Included in Base for Mean lement

198 184 Chapter 8 Case Value in Signs Variable Value in Visits Variable Included in Axis Base in Unfiltered Table 2 {No} Null Yes No 3 {Dont_Know} 5 Yes Yes 4 Null 2 No No 5 {} Null Yes No Included in Base for Mean lement Notes: When working with the hierarchical view of the data, empty levels are considered to be Null and are not counted in the base. See the seventh example table in xamples Showing Results Generated at Different Levels for more information. Working with Built-in Bases Sometimes variables (such as those in a IBM SPSS Quanvert database) have bases actually built into the variable. Built-in bases sometimes contain filtering, which may, for example, exclude cases in a Don t know or Not answered category. When one of these bases appears in a variable, IBM SPSS Data Collection Survey Reporter does not add an autobase. Note that when you select the categories and other items in a variable that you want to include in a table, you need to explicitly specify any built-in bases if you want to include them. If you do not, Survey Reporter automatically adds an autobase to ensure that the axis has a base. For example, the Museum Quanvert sample database has a base built into all of the categorical variables. Suppose that you create a table of remember by gender and use the dit Table Variable dialog box to edit the two variablesasfollows: In the remember variable, delete all of the items except the Base, Dinosaurs, andfossils categories. In the gender variable, delete the Base only. In the table, the side (which is based on the remember variable) will include the Quanvert base, because it is explicitly included in the specification for the variable, whereas the top (which is basedonthegender variable) will not, because it is not included in the specification. Therefore, Survey Reporter will create an autobase for the top but not for the side. Both of the bases in the table have the default label of Base and so the fact that one is an autobase and the other is the built-in Quanvert base is not immediately obvious simply from looking at the table. Note that when you create a new variable based on an existing variable that contains built-in special items, the special items are not copied to the new variable. For more information, see the topiccreatingnewvariablesinchapter7onp. 149.

199 185 Base Rows and Columns xcluding Information from the Base You can exclude particular categories and other items from the calculation of the base, while still including the responses in rows or columns in the table. For categories, you can do this by setting the IncludeInBasepropertyofthecategorytoNointheProperties pane of the dit Variable dialog box. This prevents the value for the category from being counted in the base, and automatically ensures that any summary statistics calculated from the base also exclude the category. The following table shows the results of excluding the Other category from the base: Figure 8-5 Table showing museums by gender This example is based on the Museum sample survey data file. Notes: Only the Count cell item is shown for excluded categories, as it is not valid to calculate an category percentage on a base if that category is not included in the base. Setting the Include In Base property to No automatically excludes the category from both base and unweighted base. Items are excluded from the closest preceding base (or unweighted base) if more than one exists. The Include In Base property has no effect on built-in bases, for example, bases in IBM SPSS Quanvert datasets. The property has no effect on items in the table other than bases and unweighted bases. It does not exclude the category from, for example, subtotals or totals. To exclude a category from a subtotal, place it after the subtotal. If you set the Include In Base property to No in a category that is part of a net, the category is excluded only from bases within the same net. The IncludeInBaseproperty can be set to No only for category type elements. Setting the IncludeInBaseproperty to No overrides any expression specified on the base.

200 186 Chapter 8 To exclude any other type of item from the base (for example, a user-defined category), you need to create an expression to exclude it, using the xpression property. Hiding the Base By default, a base is always included in each variable in your tables. However, you can choose to hide the base so that it is not shown on the table. You can do this in the Properties pane of the New Variable, dit Variable, or dit Table Variable dialog boxes, or by typing the syntax directly into the Script pane. For example, here is a table of age by gender in which the bases have been hidden. Figure 8-6 Table showing age by gender; bases hidden You can create this table in the Museum survey data file (in which age and gender are both categorical variables) as follows: Create a new table and add age to the side and gender to the top. Highlight the age variable in the table and from the menu choose Variables > dit Table Variable Choose the View Properties button on the tool bar to display the Properties pane if it is not already visible. Select the row that displays the base and, in the Properties pane, choose Hide in the Hide Options drop-down. Note: If the Script pane is visible, you can see that the script changes to the following: age{base() [IsHidden=True],..} Choose Save and Close. In the same way, select the gender variable and hide the base: gender{base() [IsHidden=True],..} Regenerate the table. Note: You can also use the hide options to hide categories and other items that appear in your tables. For more information, see the topic Hiding a category in Chapter 7 on p. 149.

201 187 Base Rows and Columns Hiding the Base in Tables xported to Microsoft xcel If you are exporting tables to Microsoft xcel spreadsheets, you can choose to hide all bases in your tables so that they do not appear in the output files. You do this by deselecting the Base values check box in the Display section on the Advanced tab of the Microsoft xcel xport dialog box. This overrides the settings in the tables.

202 Applying Statistical Tests Chapter 9 IBM SPSS Data Collection Survey Reporter provides a number of statistical tests that you can run on your tables. You can use these tests to show whether differences in the distribution of counts in tables are statistically significant or whether they are merely due to chance. The following table lists the statistical tests that are available. Note that each test has a number of requirements regarding the structure and contents of the tables on which it can be performed. Name Chi-Square Test Description This test looks at the variables on the side and the top of a table and tests whether they are independent. For example, it can be used to show whether or not variations in political opinions depend on the respondent s age. Column Proportions Test Column Means Test This test looks at the rows of a table independently and compares pairs of columns, testing whether the proportion of respondents in one column is significantly different from the proportion in the other column. The proportion is the count in the cell divided by the base for the column. This test looks at means that are presented in a row of a table and compares pairs of columns, testing whether the mean in one column is significantly different from the mean in the other column. Paired Preference Test This test deals with each column independently and compares pairs of rows to see whether the figures in each pair differ significantly from one another. T-test Test This test compares the means of two variables, computes the difference between the two variables for each case, and tests to see if the average difference is significantly different from zero. Statistics Properties The following table identifies the properties supported by each statistical test. Chi-square/Fisher Column proportions (/prod diff) Column means (/prod diff) Net difference SigLevel No Yes Yes Yes Yes SigLevelLow No Yes Yes Yes Yes MinBase No Yes Yes Yes Yes SmallBase No Yes Yes Yes Yes ShowLSD No Yes Yes No No Paired Preference T-Test Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

203 189 Applying Statistical Tests UseQFormula No Yes Yes No No UseContinuityCorrection No Yes No No No Requesting Statistical Tests To add or remove a chi-square, column proportions or column means test for the table, display the Preferences tab and click the Modify button that is just above the list of statistical tests. This opens the Modify Table Statistics dialog box, in which you can add and remove tests from your table. For information on adding a paired preference test, see To Add a Paired Preference Test Figure 9-1 Preferences tab Significance Level 1. You can select the significance level that you require for the column proportions and column means tests. The options are 1%, 5%, and 10%. Significance Level 2. If you want to perform the column proportions or column means test at two levels of significance, select the second significance level. The options are 5% and 10%. Note that the value you select must be greater than that of the first significance level.

204 190 Chapter 9 Small Base. By default, tests on rows or columns where the base is above the minimum base but below 100 are carried out, but an asterisk (*) appears next to the result to indicate that the base size is small. You can enter a new value for the small base if required. Minimum Base. By default, tests are not carried out on rows or columns where the base is below 30. Two asterisks (**) are placed in the cell to indicate this. You can enter a new value for the minimum base if required. Use effective base. Select this check box if you want IBM SPSS Data Collection Survey Tabulation to use the effective base rather than the simple weighted base in statistical tests on weighted tables. This option has no effect on statistical tests run on unweighted tables. This option is selected by default. For more information, see the topic Weighted Data and the ffective Base on p The following commands are available in the menu at the top of the Preferences tab: Copy. Copies all of the settings on the Preferences tab to the Survey Tabulation clipboard. This means that you can copy the settings to another table. Paste. Overwrites all of the options on the Preferences tab with the contents of the Survey Tabulation clipboard. Set as default for new tables. Select this option if you want to define these preferences for several tables. Any new tables that you create will automatically have the same types of cell content and all of the other options defined on the Preferences tab for this table. Apply to all existing tables. Select this option if you want to define these preferences to all of your existing tables. Modify Table Statistics Dialog Box You use the Modify Table Statistics dialog box to add or remove a chi-square, column proportion, or column means statistical test on the current table. For information on adding a paired preference test, see To Add a Paired Preference Test. Figure 9-2 Modify Table Statistics dialog box

205 191 Applying Statistical Tests Available items. This lists all of the types of statistical tests that you can run on your tables. To add an item, select the item and click the Add button. Show items in this order. Lists the selected statistical tests in the order in which they will be displayed on the Preferences tab. To remove a test, select the item and click the Remove button. To move an item up the list, select the item and click Move Up. Tomoveanitemdownthelist, select the item and click Move Down. For a full list of the statistical tests that are available, see. To Open the Modify Table Statistics Dialog Box Select the Preferences tab. The chi-square, column proportion, and column mean statistical tests that have been requested for a table are listed on the Preferences tab. For information on adding a paired preference test, see To Add a Paired Preference Test. To open the Modify Table Statistics dialog box, click the Modify button that is just above the list of statistical tests. To Add or Remove a Statistical Test This topic explains how to add a column proportions, column means, or chi-square statistics test to a table. For information on adding a paired preference test, see To Add a Paired Preference Test. In the Table List, select the table for which you want to request a statistical test. The statistical tests that have been requested for a table are listed on the Preferences tab. Select the Preferences tab. Click the Modify button that is just above the list of statistical tests. This opens the Modify Table Statistics dialog box. To add a test, select it in the Available Items list and click the Add button. To remove a test, select the item in the list on the right side and click the Remove button. Click OK. This returns you to the Preferences tab. If required, change the significance level(s) and the minimum and small base values. For more information, see the topic Requesting Statistical Tests on p. 189.

206 192 Chapter 9 ToAddaPairedPreferenceTest This topic explains how to add a paired preference test to a table. For information on adding a column proportions, column means, or chi-square statistics test, see To Add or Remove a Statistical Test. You can add the paired preference test either to an axis or to a variable. Adding the test to an axis affects only the current table, while adding the test to a variable means that it is also available for use in other tables. The paired preference test is carried out at the 5% significance level. ToaddaPairedPreferenceTesttoanAxis In the Table List, select the required table, or create a new one. Select the Define tab. In the Table Definition section, select the variable to which you want to attach the test. Figure 9-3 Selecting a variable Click the dit Axis icon: Figure 9-4 dit Axis icon This opens the. From the menu at the top of the dit tab, choose Insert. This opens the. From the Available Items list, select Paired Preference Test. Click Add, thenclickok. Click OK again to close the dit Axis dialog box. Click the Populate icon. Figure 9-5 Populate icon The table displays the paired preference test.

207 193 Applying Statistical Tests To add a Paired Preference Test to a Variable In the Variable List, select the variable to which you want to attach the test. From the Variables menu, choose dit. This opens the. From the menu at the top of the dit tab, choose Insert. This opens the. From the Available Items list, select Paired Preference Test. Click Add, thenclickok. Click OK again to close the dit Variable dialog box. The variable icon in the Variable List changes to show that the variable has been edited. Create your table using the edited variable. Click the Populate icon. Figure 9-6 Populate icon The table displays the paired preference test. To View Diagnostics Information for Statistical Tests You can choose to generate diagnostics information for statistical tests you have added to your tables, and the information is written to your IBM SPSS Data Collection Interviewer Server Administration user folder, from where you can download it to your local computer or other network location. To do this you need to have Interviewer Server Administration permissions to use the Files activity. The diagnostics information is written to a file in comma-delimited format, so that you can open it in Microsoft xcel and perform calculations on the data. The file is called RawStatisticsData.csv. To generate the diagnostics information: In the View Table Options dialog box, check the Generate Raw Statistics Data box. Populate the table. To download the diagnostics information: From the main menu bar, click the Home button to return to Interviewer Server Administration: Figure 9-7 Home button IBM SPSS Data Collection Survey Tabulation gives you an option to save the table document and then you are returned to Interviewer Server Administration.

208 194 Chapter 9 In Interviewer Server Administration, select the project and then choose Files from the list of activities. In the list of files, select the RawStatisticsData.csv file. From the Actions menu, choose Download. This opens the File Download dialog box. Click Open to open the file or Save to save the file in a location of your choice. Chi-Square Test The chi-square test looks at the variables on the side and top axes of a table and tests whether they are independent. For example, it can be used to show whether or not variations in political opinions depend on the respondent s age. The test compares the actual counts in each cell with the counts that would be expected in each cell if there were no relationship between the variables. The chi-square statistic provides a summary of the discrepancy between the actual and expected counts. The greater the dependence between the two variables, the larger the discrepancy will be, so a large chi-square statistic indicates dependence between the two variables. The p value associated with the chi-square test can be distorted if any cells in the table have very low expected counts (below 5). Fisher s xact Test The chi-square test can be used for any number of rows and columns, but gives only an estimated probability value. For a table (or section of a table) that contains two rows and two columns of data, a more accurate test is Fisher s exact test,whichfinds the exact probability value for the table. Fisher s exact test is appropriate only for tables, or parts of tables, with two rows and two columns that contain values (for example, a nested section of a larger table may be valid for this test). Rows and columns with no respondent data are ignored by the test, so a table with two rows and two columns may not be valid if, for example, one of the rows has no data. Conversely, a table with three rows and two columns may be suitable for the test if one of the rows has no data. You can use this test on its own or in addition to the chi-square test. If you request the chi-square test and Fisher s exact test on the same table, a single chi-square column is used to display the results for both tests. If you request Fisher s exact test on a table that does not meet the requirements, it is not carried out. The value returned by Fisher s exact test is the two-tailed p value, which does not distinguish between significantly high and significantly low results. xample of the Chi-Square Test Sample Script File: ChiSquareAndFisherTests.mrs

209 195 Applying Statistical Tests This example script is based on themuseumsampledataset. The chi-square test in this example tests whether there is an association between respondents expectations of their visit to the museum and their age. Figure 9-8 Table showing chi-square test Notice that IBM SPSS Data Collection Survey Reporter has added two rows to the table below the rows formed from the categories of the age variable. Similarly, Survey Reporter has added a column to the right of the columns formed from the categories of the expect variable. The cell at the intersection of the first additional row and column displays the chi-square statistic. In this table, the chi-square statistic is The table also shows the p value for this chi-square value, based on the degrees of freedom for the table (you can see the degrees of freedom in the diagnostics file). In this case, the p value of indicates that there is approximately a 2.5% chance that the results are due to chance, and therefore a 97.5% probability that there is a significant relationship between respondents expectations of their visit and their age. xample of Fisher s xact Test Sample Script File: ChiSquareAndFisherTests.mrs This example script is based on themuseumsampledataset. This example tests whether having a biology qualification has any influence over whether respondents prefer the dinosaurs exhibit or the human biology exhibit. In a simple table of biology by prefer, the results appear to show that most people with no biology qualification prefer dinosaurs, whereas people with a biology qualification display no particular preference between dinosaurs and human biology. As this information is contained in two rows and two columns, you can apply Fisher s exact test to determine whether this difference is significant or simply the result of chance.

210 196 Chapter 9 Notice that although the table of biology by prefer contains three rows and two columns, IBM SPSS Data Collection Survey Reporter is able to apply Fisher s exact test because it detects that only two rows and two columns contain data and so the table meets the requirements of this test. Figure 9-9 Table showing Fisher s exact test The resulting table has an additional Fisher xact row below the rows formed from the categories of the biology variable. Similarly, an additional ChiSq column appears to the right of the columns formed from the categories of the prefer variable. The cell formed by the Fisher xact row and the ChiSq column displays the value returned by the test, which is the exact p value for the table. In this table, the value is 0.021, which indicates that there is approximately a 2% probability of the results in this table occurring by chance, and therefore a 98% percent probability that the apparent difference in preference between those with and those without a biology qualification is statistically significant. Chi-square Test and Fisher s xact Test You can apply both the chi-square test and Fisher s exact test to the same table. For example, you may decide to apply both tests on a table with several sections so that Fisher s exact test will display anexactp value in those sections where it is possible to do so, while the value for the chi-square test will still be available in the other sections of the table. In this table the top section has more than two rows and is therefore unsuitable for Fisher s exact test, so only the chi-square result is calculated. The bottom section has two rows and two columns of data, so the results for both Fisher s exact test and the chi-square test are displayed.

211 197 Applying Statistical Tests Figure 9-10 Table showing chi-square and Fisher s exact tests Details and Restrictions of the Chi-Square Test IBM SPSS Data Collection Survey Reporter displays a message if you defineachi-squaretest on an unsuitable table or if you change a table that has a chi-square test definedsothatitisno longer suitable for the test. When this happens, you can either adjust the table so that it conforms to the restrictions, or you can remove the test from the table. However, sometimes Survey Reporter is unable to determine that a table or a section of a table is unsuitable for the test until it actually attempts to perform it for example, when a table has only two category columns and all of the values in one of those columns are zero. When that happens, Survey Reporter simply skips the test and leaves the chi-square and p value rows blank. Multiple response variables. This test is not suitable for tables that include a multiple response variable. Hierarchical data. This test is unsuitable for running on lower level data when you are working with hierarchical data. For more information, see the topic Hierarchical Data on p. 257.

212 198 Chapter 9 Rows and columns For the chi-square test, the variables on the side and top axes must have at least two categories. Survey Reporter does not perform the test on rows and columns in which all of the values are zero or on rows and columns that are formed from non-category elements, such as bases and means. Fisher s exact test is carried out only on tables that have exactly two categories containing data on the top and side axes of the table (or on a subsection of the table, such as that formed by a nested or concatenated table). Nested and concatenated tables. Thechi-squaretestcomparesthe columns and rows formed from the categories of two variables one on the side axis and one on the top axis. If there is more than one variable on either the side or the top axis, the test is performed separately for each combination of variables at the innermost nesting level. This means that the innermost child variables must have at least two categories. Built-in bases. This test is not suitable for tables that include variables that contain more than one built-in base. Two by two tables. When performing the chi-square test on a table or a section of a table that has two category columns and two category rows, Survey Reporter computes Yates corrected chi-square (continuity correction). When performing the Yates corrected chi-square, Survey Reporter also computes Fisher s exact test. However, the results of Fisher s exact test are shown only in the diagnostics data and not on the table itself (unless you have also requested Fisher s exact test on the table). xcluded lements. The IncludeInBase=False property has no effect on the chi-square test. If a chi-square test is carried out on a table containing categories that are excluded from the base using IncludeInBase=False, the calculation includes rows and columns corresponding to the excluded categories. Statistical Formula for the Chi-Square Test The following table shows the notation used in this topic. Notation Description Observed frequency in row i, column j. Thisvalue is weighted in a weighted table, unweighted in an unweighted table. Number of rows contributing to the test. Number of columns contributing to the test. The total in row i:

213 199 Applying Statistical Tests Notation Description The total in column j: The total in the table or section of the table being tested: The expected value in the table or section of the table being tested: where, for Pearson s formula: and for the Yates correction: The degrees of freedom are: For details of Fisher s exact test, see Appendix 5, p , SPSS 7.5 Statistical Algorithms (1997), Chicago, IL: SPSS Inc. ISBN Column Proportions Test The column proportions test looks at the rows of a table independently and compares pairs of columns, testing whether the proportion of respondents in one column is significantly different from the proportion in the other column. The proportion is the count in the cell divided by the base for the column.

214 200 Chapter 9 IBM SPSS Data Collection Survey Reporter automatically assigns a one-character ID to each column in the test. When there is a difference between any pair of proportions at the chosen significance level, Survey Reporter displays the ID of the column that contains the smaller proportion below the cell contents of the cell that contains the larger proportion. Note: Column IDs are only applied to visible table elements. Hidden elements are not taken in consideration when defining a Column IDs as a string. xamples of the Column Proportions Test Sample Script File: ColumnProportionsTest.mrs This example script is based on themuseumsampledataset. The first column proportions test in this example tests whether there are any significant differences in the proportions of male and female respondents who found the different galleries most interesting.

215 201 Applying Statistical Tests Figure 9-11 Table showing column proportions test Notice that IBM SPSS Data Collection Survey Reporter has assigned IDs of A to the Male column and B to the Female column and that these are displayed below the column headings. Notice the B below the cell contents in the Male cell of the Insects row, and the A below the cell contents in the Female cell of the Human biology row. For the Insects row, this indicates that the proportion of male respondents is higher than the proportion of female respondents and that this difference in proportions is statistically significant at the 5% significance level. For the Human biology row, this indicates that the proportion of female respondents is higher than the proportion of male respondents and that this difference in proportions is statistically significant at the 5% significance level.

216 202 Chapter 9 The column proportions test in this table shows us that, although the proportions of male and female respondents who found the different galleries most interesting vary, the differences are statistically significant only for the Insects and Human biology galleries. The differences in the preferences for all of the other galleries can be explained by chance. The next example tests whether there are any significant differences in the proportions of male and female respondents who visited or planned to visit other museums. Figure 9-12 Table showing column proportions test Notice that Survey Reporter has assignedidsofatothemale column and B to the Female column and that these are displayed below the column headings. Notice the B below the cell contents in the Male cell of the National Museum of Science row, and the A below the cell contents in the Female cell of the National Art Gallery row. For the National Museum of Science row, this indicates that the proportion of male respondents is higher than the proportion of female respondents and that this difference in proportions is statistically significant at the 5% significance level. FortheNational Art Gallery row, this indicates that the proportion of female respondents is higher than the proportion of male respondents and that this difference in proportions is statistically significant at the 5% significance level. The column proportions test in this table shows us that, although the proportions of male and female respondents who found the different galleries most interesting vary, the differences are statistically significant only for National Museum of Science and National Art Gallery. The differences for all of the other named museums can be explained by chance.

217 203 Applying Statistical Tests xamples of Testing Different Columns The next example shows the results of a column proportions test using the default columns, on a table with Biology nested within Before on the top axis: Figure 9-13 Column Proportions test with default columns tested This example tests the default selection of columns; that is, it tests all columns in each section of the table against each other. In this case, the test indicates whether there are any significant differences between the expectations of those who have a biology qualification and those who do not. The results show a significant difference in the expectation of general knowledge and education, between those with and without a qualification who have visited the museum before (columns C and D). However, in this table, it is also possible that we might want to concentrate on significant differences between those who have been to the museum before and those who have not. The following example tests this: "C/, D/F"

218 204 Chapter 9 Figure 9-14 Column proportions test with selected columns The results show a significant difference in the expectation of education for children, between people with no biology qualification who have visited the museum before and those who have not (columns D and F). xample of Defining Column IDs as a String Starting with IBM SPSS Data Collection Base Professional 5.6 you can define column IDs as a string using the ColumnsID property. ach character in the string is used to allocate a column ID, with a period or space character used to indicate that an ID should not be allocated. A character needs to be added to the ID s string for each column, even if the column is hidden. When allocating column IDs a character should also be added for the base columns. For the table below, the column IDs could be set as follows to test Yes-Male against No-Male, and Yes-Female against No-Female: Table.Statistics.ColumnIDs = "...MF.NG" Table.Statistics.TestColumns = "M/N, F/G"

219 205 Applying Statistical Tests Figure 9-15 Column Proportions Test with New Column IDs Note: Column IDs are only applied to visible table elements. Hidden elements are not taken in consideration when defining a Column IDs as a string. Details and Restrictions of the Column Proportions Test IBM SPSS Data Collection Survey Reporter displays a message if you define a column proportions test on an unsuitable table or if you change a table that has a column proportions test defined so that it is no longer suitable for the test. When this happens, you can either adjust the table so that it conforms to the restrictions described here, or you can remove the test from the table. However, sometimes Survey Reporter is unable to determine that a table or a section of a table is unsuitable for the test until it actually attempts to perform it for example, when a table has only two category columns and all of the values in one of those columns are zero. When this happens, Survey Reporter simply skips the test. Hierarchical data. This test is unsuitable for running on lower level data when you are working with hierarchical data. For more information, see the topic Hierarchical Data on p Grids. It is possible to run this test on grids, provided that the test is carried out on a grid table structured in the format: rating[..].column * rating This test is suitable for running on grid tables in the following format when you set the level of the table to be the top (for example, TableDoc.Table1.Level="hdata"): rating * rating[..].column Weighting. This test is unsuitable for running when weighting is applied to individual columns or rows. Rows. This test compares the proportions in each row that are formed from a variable category. The test is not performed on rows that are formed from non-category elements, such as bases and means.

220 206 Chapter 9 Columns. For each category row, the test compares pairs of columns that are formed from variable categories, testing whether the proportion of respondents in one column is significantly different from the proportion in the other column. Survey Reporter does not test columns that are formed from non-category elements or columns in which all of the values are zero. The test cannot be performed on tables that contain more than 52 category columns if you request one significance level, or 26 category columns if you request two significance levels, and it needs a minimum of two category columns. Built-in Column Proportions tests. If a column proportions test is included in the metadata for a variable, the test is performed only if the variable is added as a single variable. If it is nested or concatenated with other variables, the built-in test is ignored to prevent possible inconsistencies in the results, and you must explicitly specify a column proportions test for the whole axis. Nested tables. If there is nesting on the top axis, the test is performed separately for each set of columns that is formed from the categories of the innermost child variables. This means that the innermost child variables must have at least two categories. Nesting on the side axis does not change the test each category row is always tested. Concatenated tables. If there is concatenation on the top axis, the test is performed separately for each set of columns that is formed from the categories of a concatenated variable. Concatenation on the side axis does not change the test each category row is always tested. Built-in bases. If any of the variables on the top axis has more than one base, the test is performed separately for the columns formed from the categories before and after each base. Sample size. This test relies on a large sample, which means that it may not be valid for a small sample for example, fewer than about 30 cases. Survey Reporter checks for small sample sizes, and does not carry out the test on columns with a base below 30. You can change the minimum sample size if required, by entering a new value in the Minimum Base field in the Statistics tab of the Table Properties dialog box. Multiple response variables. When there is a multiple response variable on the top axis, Survey Reporter performs the overlap adjustment. Two-tailed test. This is a two-tailed test, which means that it reports all significant differences between the proportions in all of the columns regardless of which columns contain the greater proportions. xcluded elements. The column proportions test is not carried out for rows that have been excluded fromthebaseusingtheincludeinbase=false property. The column proportions test is carried out for columns that have been excluded from the base using the IncludeInBase=False property. Overlap formula. ach axis can be derived from either an axis expression or an MDM variable. When an axis is derived from an axis expression, TOM will honor the MaxResponses property. When the MaxResponses value is greater or equal to 2, TOM regards the axis as overlapped. Considering that the MaxResponses default value is 2, each axis is in an overlap state by default. When an axis is derived from an MDM variable, TOM will honor the variable s ffectivemaxvalue property. When the ffectivemaxvalue value is greater or equal to 2, TOM regards the axis as overlapped. When there are any sub-axis that are overlapped for a table s side and top, TOM regards the side or top as overlapped.

221 207 Applying Statistical Tests When both the side and top are overlapped for a table, and UseGridOverlapFormula is true, the grid overlap formula is applied to the table. The normal overlap formula is applied when the table s top is overlapped, otherwise the standard formula is used. Refer to the following topics for more information regarding overlap: TOM.IStatistics.UseGridOverlapFormula TOM.IAxis.MaxResponses../com.spss.ddl/MDM/IField_ffectiveMaxValue.html Statistical Formula for the Column Proportions Test The column proportions test is performed separately for each relevant pair of columns within each relevant row and so the formula is presented in terms of one row and one pair of columns. The following table shows the notation used in this topic. Notation Description Weighted base in column i. Sum of squared weights for column i. Weighted count in this row for column i. Weighted base for the overlap. Sum of squared weights for the overlap. Count in this row for the overlap. The proportion in each column i is If the effective base is being used, the effective base in each column i is Otherwise The test is not performed if: w i <= 0

222 208 Chapter 9 The effective base is being used and q i <= 0 The proportions in the two columns being tested are identical The combined proportion for a pair of columns, 1 and 2, is The covariance term, v, and the effective base, e o, are both set to 0 if: Thedataarenotoverlapping The data are overlapping and w o <= 0 The data are overlapping and the effective base is being used and q o <= 0 Otherwise Figure 9-16 Figure 9-17 Figure 9-18 xcept for grids, Z always reduces to the value of 1.0. For grids, the formula for Z is: Figure 9-19 Where r 0 = the count for this row in the overlap r 1 = the count for this row in column 1 for respondents in both columns r 2 = the count for this row in column 2 for respondents in both columns and w 0 is the base in the overlap, that is, the number of respondents who were asked both columns. The t value is calculated as

223 209 Applying Statistical Tests Figure 9-20 where, The degrees of freedom, DF, are DF = e 1 + e 2 - e 0-2 The absolute value of t together with the degrees of freedom are used to calculate the probability, p, forthet value. If p is less than the significance level requested, the proportions in the two columns are deemed to be significantly different. Note: The grid overlap formula is applied when the columns have respondents in common, but some (or all) appear in different rows. The grid table normally complies with the rule that there is at least a multiple response categorical variable, or a grid or loop iterator, on both the side and the top. Column Means Test The column means test looks at means that are presented in a row of a table and compares pairs of columns, testing whether the mean in one column is significantly different from the mean in the other column. IBM SPSS Data Collection Survey Reporter automatically assigns an ID to each column in the test. When there is a difference between any pair of means at the chosen significance level, Survey Reporter displays the ID of the column that contains the smaller value below the cell contents of the cellthatcontainsthelargervalue. Note that the means must be formed from a mean element in the axis rather than from mean values that are created using the Mean cell contents option. For full details about the types of tables that are suitable for this test and what happens when there is nesting or concatenation, see. The Least Significant Difference When you add a column means test to a table, you can optionally display a least significant difference column for each row of the table. This is the variance for all specified columns at once, rather than for the pairs of columns that the column means test uses. When the column means test is applied to a group of columns (for example, ABC), each pair of columns (AB, AC, BC) is tested separately to see if the mean values are significantly different. The least significant difference calculation uses the data from all columnsinthegrouptocalculate the smallest difference in means that would be significant at the requested significance level.

224 210 Chapter 9 To display the least significant difference column on a table, check the Show least significant difference box on the Statistics tab of the Table Properties dialog box. Notes The least significant difference calculation is available only for independent samples (that is, for non-overlapping columns). The least significant difference test is available only for tables with a significance level of 1, 5, 10, 15, 20, 25, 32, or 50. The least significant difference is available with nesting and concatenating on the top axis. It is not available for tables that use the TestColumns option to carry out non-default column testing. The characters XXXXX are displayed instead of the result if the table does not meet these conditions. This test is appropriate only when the groups being tested have similar base sizes. If the base sizes differ by more than 25%, the test is not suitable for the table. xamples of the Column Means Test Sample Script File: QuanvertTables.mrs This example script is based on themuseumsampledataset. The column means test in this example tests whether there are any significant differences between: The mean age of all respondents who do and do not have a biology qualification The mean age of the male respondents who do and do not have a biology qualification The mean age of the female respondents who do and do not have a biology qualification

225 211 Applying Statistical Tests Figure 9-21 Table showing column means test Notice that IBM SPSS Data Collection Survey Reporter has assigned IDs to all of the columns in the test. Because this is a nested table, the Yes and No columns formed from the categories of the child variable (biology) are repeated for each element of the parent variable (gender). Survey Reporter performs the column means test separately for each set of columns formed from the categories of the biology variable. Notice how this is reflectedinthefootnotetext. The first set of Yes and No columns in the table (with IDs A and B respectively) are nested within thebase column of thegenderparent variable. They therefore relate to all of the respondents, both male and female. The A below the cell contents in the Mean age row in the No column indicates that the mean age of the respondents in this column is higher than the mean age of the respondents in the Yes column and that the difference is statistically significant at the 5% significance level. The second set of Yes and No columns in the table (with IDs C and D respectively) relate to the male respondents. The C in the No column also indicates that the mean age of the respondents in this column is higher than the mean age of the respondents in the Yes column and that the difference is statistically significant at the 5% significance level.

226 212 Chapter 9 The third set of Yes and No columns in the table (with IDs and F respectively) relate to the female respondents. Survey Reporter has not displayed any IDs in the mean age row in these columns, because the difference in mean age is not statistically significantatthe5%significance level. The column means test in this table shows us that the difference in mean age between the respondents who have and do not have a biology qualification is significant at the 5% significance level, but that this is only true for the male respondents and the whole sample. It is not true for the female respondents. xample of Testing Different Columns The previous example describes the results of testing the default selection of columns. However, it is possible to test other combinations of columns instead. For example, you may want to test for significant differences between: The mean age of holders of a biology qualificationwhoaremaleandthosewhoarefemale The mean age of those without a biology qualification who are male and those who are female You can do this by specifying the columns you want to test: "C/, D/F"

227 213 Applying Statistical Tests This example shows the results of this test: Figure 9-22 Column means test on selected columns The result shows that there is a significant difference between the mean ages of male and female holders of a biology qualification (columns C and ). xample of Testing at Two Significance Levels In the next example, two levels of significance have been specified, to test the same table both at the 5% (higher) and the 10% (lower) level.

228 214 Chapter 9 Figure 9-23 Table showing column means test at 2 levels of significance Notice that in addition to the IDs assigned to the cells in the previous example, in the third set of Yes and No columns in the table, relating to the female respondents, there is now a lowercase e in the No column. This indicates that the mean age of the respondents in this column is higher than the mean age of the respondents in the Yes column and that the difference is statistically significant at the 10% level. xample Showing the Least Significant Difference Column Sample Script File: QuanvertTables.mrs This example script is based on themuseumsampledataset.

229 215 Applying Statistical Tests This example is based on the first table in xamples of the Column Means Test. Thecolumn means test is run on the same table specification with the same significance level. In addition, a least significant difference column is added to the table. Here is the table: Figure 9-24 Table showing column means test with least significant difference Notice that an additional column has been added in each section of the table. In the Mean age row, the column contains the lowest value that would be required for the difference between columns to be significant. For example, in the Female section of the table, the columns ( and F) are not marked as significantly different. The difference between the two columns and F is 3.0. The least significant difference value for this section shows that, in order to be significant, the columns in this section would need to differ by at least Details and Restrictions of the Column Means Test IBM SPSS Data Collection Survey Reporter displays a message if you define a column means test on an unsuitable table or if you change a table that has a column means test definedsothat it is no longer suitable for the test. When this happens, you can either adjust the table so that it conforms to the restrictions described here, or you can remove the test from the table. However, sometimes Survey Reporter is unable to determine that a table or a section of a table is unsuitable for the test until it actually attempts to perform it. When this happens, Survey Reporter simply skips the test.

230 216 Chapter 9 Hierarchical data. This test is unsuitable for running on lower level data when you are working with hierarchical data. For more information, see the topic Hierarchical Data on p Grids. It is possible to run this test on grids, provided that the test is carried out on a grid table structured in the format: rating[..].column * rating This test is unsuitable for running on grid tables in the format: rating * rating[..].column Weighting. This test is unsuitable for running when weighting is applied to individual columns or rows. Mean rows. Survey Reporter can perform this test only if there is a mean row on the side axis. The mean row must be formed from a mean element. This can be a built-in mean or a mean added to the variable using the dit Variable window. The test does not test mean values created using the Mean cell contents option. The test does not test mean values created using the Mean cell contents option. Columns. For each mean row, the test compares pairs of columns that are formed from variable categories. Survey Reporter does not compare columns that are formed from non-category elements or columns in which the number of cases contributing to the mean is zero. The test cannot be performed on tables that contain more than 52 category columns if you request one significance level, or 26 category columns if you request two significance levels, and it needs a minimum of two category columns. Built-in Column Means tests. If a column means test is included in the metadata for a variable, the test is performed only if the variable is added as a single variable. If it is nested or concatenated with other variables, the built-in test is ignored to prevent possible inconsistencies in the results, and you must explicitly specify a column means test for the whole axis. Nested tables. If there is nesting on the top axis, the test is performed separately for each set of columns that are formed from the categories of the innermost child variables. This means that the innermost child variables must have at least two categories. Nesting on the side axis does not change the test each mean row is always tested. Concatenated tables. If there is concatenation on the top axis, the test is performed separately for each set of columns that are formed from the categories of a concatenated variable. Concatenation on the side axis does not change the test each mean row is always tested. Built-in bases. If any of the variables on the top axis has more than one base element, the test will be performed separately for the columns formed from the categories before and after each base. Sample size. This test relies on a central limit theorem approximation to the normal distribution. This means that a large sample (generally at least 30 cases) is required if the data is not distributed normally. However, when the data is distributed normally, a large sample is not necessary. Survey Reporter checks for small sample sizes, and does not carry out the test on columns with a base

231 217 Applying Statistical Tests below 30. You can change the minimum sample size if required, by entering a new value in the Minimum Base field in the Statistics tab of the Table Properties dialog box. Multiple response variables. When there is a multiple response variable on the top axis, Survey Reporter performs the overlap adjustment. xcluded lements. The column means test is performed whether or not it is carried out on a table containing elements that are excluded from the base using IncludeInBase=False. The calculation includes rows and columns corresponding to the excluded elements. Overlap formula. ach axis can be derived from either an axis expression or an MDM variable. When an axis is derived from an axis expression, TOM will honor the MaxResponses property. When the MaxResponses value is greater or equal to 2, TOM regards the axis as overlapped. Considering that the MaxResponses default value is 2, each axis is in an overlap state by default. When an axis is derived from an MDM variable, TOM will honor the variable s ffectivemaxvalue property. When the ffectivemaxvalue value is greater or equal to 2, TOM regards the axis as overlapped. When there are any sub-axis that are overlapped for a table s side and top, TOM regards the side or top as overlapped. When both the side and top are overlapped for a table, and UseGridOverlapFormula is true, the grid overlap formula is applied to the table. The normal overlap formula is applied when the table s top is overlapped, otherwise the standard formula is used. Refer to the following topics for more information regarding overlap: TOM.IStatistics.UseGridOverlapFormula TOM.IAxis.MaxResponses../com.spss.ddl/MDM/IField_ffectiveMaxValue.html Statistical Formula for the Column Means Test The column means test is performed separately for each relevant pair of columns within a row that contains mean values and so the formula is presented in terms of one row and one pair of columns. The following table shows the notation used in this topic. Notation Description Weighted count of cases contributing to the mean in column i. Sum of squared weights for column i. Weighted count of cases contributing to the mean for the overlap. Sum of squared weights for the overlap.

232 218 Chapter 9 Notation Description Weighted sum of the values in column i. Weighted sum of the squared values in column i. The mean in each column i is If the effective base is being used, the effective base in each column i is Otherwise The test is not performed if: w i <= 0 The effective base is being used and q i <= 0 Themeanvaluesinthetwocolumnsbeingtestedareidentical The sample variance in column i is If we set Then the pooled estimate of the population variance is The t value is

233 219 Applying Statistical Tests With no overlap, Z and e o are both zero. With overlap, Z is 1.0, except in the case of grids, where it is: Figure 9-25 where: X 12 is the weighted sum, for respondents in both columns, of the value in column 1 multiplied by the value in column 2 all X and Y terms in Z refer to respondents who are in both columns. The degrees of freedom, DF, are DF = e 1 + e 2 - e 0-2 Note: The grid overlap formula is applied when the columns have respondents in common, but some (or all) appear in different rows. The grid table normally complies with the rule that there is at least a multiple response categorical variable, or a grid or loop iterator, on both the side and the top. Statistical Formula for the Least Significant Difference Test The formula for the least significant difference value for independent values is as follows: Notation Description Weighted count of cases contributing to the mean in column i. Weighted sum of the values in column i. Weighted sum of the squared values in column i. NCOL The number of columns in the group. The degrees of freedom are: Figure 9-26 degrees of freedom

234 220 Chapter 9 and the LSD value is: Figure 9-27 lsd formula where MS is the mean square: Figure 9-28 HM is the harmonic mean: Figure 9-29 and SIGVAL is the critical value of T for DOF degrees of freedom at the significance level definedbytheuser. Net Difference Test The net difference test deals with each row independently and compares the difference between the proportions in one pair of columns with the difference between the proportions in another pair of columns. The result is tested for significance at the selected level. The results of the test are displayed in a separate column. For example, if the difference between the proportion of women preferring Brand A before and after testing is larger than those preferring Brand B, and the difference between those two proportionsissignificant at the selected level, the result is flagged as significant and the letter S is displayed in the net difference column of the row for women. When you specify a net difference test, to specify which columns to test and where to place the result, you must also add a net difference item to the variable. If the table is nested, this must be in the innermost nesting level. IBM SPSS Data Collection Survey Reporter carries out the test on the four columns preceding the net difference item.

235 221 Applying Statistical Tests How the results are displayed The null hypothesis is that the two figures being compared are equal, that is, the difference between them is zero. The following table shows the symbols that are displayed on the table for different results. Result Significant at the selected level Significant at the lower selected level but not the higher level Not significant at the selected level(s), but significant at the 32% level Not significant at the 32% level Displayed S s NS That is: If the result of the test is significantatthespecified significance level, Survey Reporter places the letter S in the additional column. If you run the test at two significance levels, results that are significant at the higher level are displayed using an uppercase S, and results that are significant at the lower level are displayed using a lowercase s. If the result of the test is not significant at the selected level(s), but is significant at the 32% significance level (equivalent to a p valueof0.32oraconfidence level of 68%, indicating that the difference between the figures being compared is at least one standard deviation away from zero) Survey Reporter places the letters NS in the additional column. If the difference between the figures being compared is not significant at the 32% significance level (that is, the difference is less than one standard deviation away from zero) Survey Reporter places the letter in the additional column. xample of the Net Difference Test Sample Script File: NetDifferenceTest.mrs This example script is based on the SkiDemo sample data set. In this example, based on the SkiDemo survey installed with the IBM SPSS Data Collection Developer Library, a new variable that combines categories from the ownski and repeat variables forms the top of the table and the age variable forms the side.

236 222 Chapter 9 Here is the resulting table: Figure 9-30 Net difference test The test is based on proportions; that is, it takes the value in each row as a proportion of the total for the whole column. For each row (socio-economic class in this example) it finds the difference for this value (the proportion of the whole column) between those who have not visited the resort before and those who have visited before. It does this separately for two groups of people, those who own their skis (the first and second columns) and those who rent them (the third and fourth columns). It then finds the overall difference between the two groups of people, ski owners and ski renters. This results in a single value for each row, which is then tested against the base for the column to see if it is significantly different from the column as a whole. If the result is found to be significant for any row, an S is placed in the net difference column for that row. The net difference test in this example shows that there is a significant difference for the AB and the C2 socio-economic classes. Details and Restrictions of the Net Difference Test Columns to be tested must be defined in groups of four. If there are more than four categories the net difference test is carried out on the preceding four category elements nearest the net difference element. If there are fewer than fourcategories, the net difference test is not carried out. The net difference test is not available across the different sections of a table that are created by nesting and concatenation. When you specify a net difference test, you must also add a net difference element to the top of the table. If the table is nested, this must be in the innermost nesting level.

237 223 Applying Statistical Tests Statistical Formula for the Net Difference Test The following table shows the formulae used for conducting the net difference test in IBM SPSS Data Collection Survey Reporter. Formula for Proportions For any row, and any of the four columns being tested (i=1,2,3, and 4): Notation Description W i Sum of the weights (weighted base) for column i. Q i Sum of the squared weights for column i. i =(W i * W i )/Q i ffective base for column i. P i Proportion in column i For a table with overlap or a grid table, and any pair of columns from the four being tested (i and j=1,2,3, and 4): Notation W ij Q ij ij =(W ij * W ij )/Q ij P ij Description Sum of the weights (weighted base) for respondents in both columns. Sum of the squared weights for respondents in both columns. ffective base for respondents in both columns. Proportion for respondents belonging in the row being tested for both columns. The formula is: Figure 9-31 where numer =(P 3 - P 4 )-(P 1 - P 2 ) and for a non-grid, non-overlap table Figure 9-32 For a table with overlap or a grid table

238 224 Chapter 9 Figure 9-33 where Figure 9-34 The degrees of freedom are: Figure 9-35 where, for a non-grid, non-overlap table Figure 9-36 and Figure 9-37 For a table with overlap or a grid table Figure 9-38 and Figure 9-39

239 225 Applying Statistical Tests Formula for Means For any row, and any of the four columns being tested (i=1,2,3, and 4): Notation Description W i Sum of the weights (weighted base) for column i. Q i Sum of the squared weights for column i. i =(W i * W i )/Q i ffective base for column i. X i sum of values for column i Y i sum of squared values for column i M i mean for column i=x i /W i The values may be either numeric values or factor values. For a table with overlap or a grid table, and any pair of columns from the four being tested (i and j=1,2,3, and 4): Notation W ij Q ij ij =(W ij * W ij )/Q ij Description Sum of the weights (weighted base) for respondents in both columns. Sum of the squared weights for respondents in both columns. ffective base for respondents in both columns. The intermediate term SX is: Figure 9-40 The tstat is Figure 9-41 where numer =(M 3 - M 4 )-(M 1 - M 2 ) and for a grid, non-overlap table,

240 226 Chapter 9 Figure 9-42 For a table with overlap or a grid table Figure 9-43 where Figure 9-44 For a non-grid table with overlap, R ij reduces to 1. Grid tables For a grid table, it is not possible to display the net difference if the mean is a numeric mean rather than a factor mean. In this case, an error is returned. For a grid table with factor means: Notation X i* X *j Y i* Y *j Y ij Description The weighted sum of factors for column i for all respondents belonging in the mean for column i and in the base of column j. The weighted sum of factors for column j for all respondents belonging in the mean for column j and in the base of column i. The weighted sum of squared factors for column i for all respondents belonging in the mean for column i and in the base of column j The weighted sum of squared factors for column j for all respondents belonging in the mean for column j and in the base of column i The weighted sum of (factor for column i) * (factor for column j) for all respondents belonging in the mean for both columns. Using the above terms

241 227 Applying Statistical Tests Figure 9-45 where Figure 9-46 Degrees of freedom The degrees of freedom are: Figure 9-47 where, for a non-grid, non-overlap table: Figure 9-48 and Figure 9-49 For a table with overlap or a grid table: Figure 9-50 and

242 228 Chapter 9 Figure 9-51 For more on the theory of overlapping samples, see Kish, L (1965), Survey Sampling, NewYork: John Wiley and Sons. ISBN X. Paired Preference Test The paired preference test compares pairs of values to see whether the figures in each pair differ significantly from each other. The paired preference item is usually specified in a row. However, you can specify it in a column. The test works as follows: If specified in a row, the paired preference test deals with each column independently and compares pairs of rows. The test needs a minimum of two rows to be able to compare their figures. If specified in a column, the paired preference test deals with each row independently and compares pairs of columns. The test needs a minimum of two columns to be able to compare their figures. For example, if the proportion of women preferring Brand A is larger than those preferring Brand B, and the difference between the two proportions is significant at the selected level, the letter S is displayed in the paired preference row of the column for women. To specify which rows to test and where to place the result, you need to add a paired preference item to the row or column. For more information, see the topic Adding a Paired Preference Test or a Net Difference Test on p When a paired preference element is placed in a row or column, IBM SPSS Data Collection Survey Reporter searches for the nearest two categories preceding the paired preference item, and carries out the paired preference test on those two categories. For the purposes of the paired preference test the following element types are classed as category elements: category expression net combine numeric The result of the test is placed at the position of the paired preference row or column. The following information assumes specification as a column.

243 229 Applying Statistical Tests How the results are displayed The null hypothesis is that the two figures being compared are equal, that is, the difference between them is zero. The following table shows the symbols that are displayed on the table for different results. Result Significant at the selected level Significant at the lower selected level but not the higher level Not significant at the selected level(s), but significant at the 32% level Not significant at the 32% level Displayed S s NS That is: If the result of the test is significantatthespecified significance level, Survey Reporter places the letter S in the additional column. If you run the test at two significance levels, results that are significant at the higher level are displayed using an uppercase S, and results that are significant at the lower level are displayed using a lowercase s. If the result of the test is not significant at the selected level(s), but is significant at the 32% significance level (equivalent to a p valueof0.32oraconfidence level of 68%, indicating that the difference between the figures being compared is at least one standard deviation away from zero) Survey Reporter places the letters NS in the additional column. If the difference between the figures being compared is not significant at the 32% significance level (that is, the difference is less than one standard deviation away from zero) Survey Reporter places the letter in the additional column. xamples of the Paired Preference Test The first paired preference test in this example is carried out on the rows of the table. It tests whether there is a significant difference between the numbers of people who prefer dinosaurs and the numbers preferring human biology. The difference is seen to be significant for males and not significant for females.

244 230 Chapter 9 Figure 9-52 Table showing paired preference test The paired preference test is usually carried out on rows. However, you can also carry out the test on columns. In this example, Age is nested within Gender. As this would create a very wide table if this were on the top of the table, Prefer is placed on the top and the test is carried out on columns.

245 231 Applying Statistical Tests Figure 9-53 Table showing paired preference test on columns Running the Paired Preference Test at Two Significance Levels You can carry out the paired preference test at two significance levels in the same table. The next example creates a table with the Prefer variable on the side of the table, and the Similar variable on the top of the table, with a paired preference test applied to the rows of the table. This tests whether there is a significant difference between the numbers who prefer dinosaurs and those who prefer human biology, broken down by whether the respondents have visited similar museums before. This test is run at the 5% significance level, representing a 95% chance that the results are statistically significant and not just due to chance.

246 232 Chapter 9 Figure 9-54 Table showing paired preference test at one significance level Notice that for those who answered No, the letters NS are placed in the Paired Preference column, indicating that at the 5% significance level the difference in the numbers who prefer dinosaurs and those who prefer biology is not significant. The next example shows the table when the test is run at both the 5% and the 10% level. The 10% significance level indicates a lower level of confidence, representing a 90% chance that the results are statistically significant and not just due to chance. Figure 9-55 Table showing paired preference test at two significance levels Notice that for those who answered No the lowercase letter s is placed in the Paired Preference column. This indicates that the difference in numbers of those who prefer dinosaurs and those who prefer biology is significant at the lower (10%) level.

247 233 Applying Statistical Tests Details and Restrictions of the Paired Preference Test The paired preference test is not suitable for all tables. It is up to you to make sure that the data in the table is generally suitable for testing, that the sample size is suitable, etc. The paired preference element is usually specified in a row to compare two rows for each column independently. However, you can specify it in a column to compare two columns for each row independently. The following information assumes specification as a row. Hierarchical data. This test is unsuitable for running on lower level data when you are working with hierarchical data. For more information, see the topic Hierarchical Data on p Rows. The test searches for the nearest two categories preceding the paired preference row (or column) to perform the test on, but it stops searching at a base or another paired preference item, and if it has not found two categories by then it does not perform the test. The test ignores categories at a different net level. Columns. The test works independently on all columns. Sample size. This test relies on a large sample, which means that it may not be valid for a small sample for example, fewer than about 30 cases. IBM SPSS Data Collection Survey Reporter checks for small sample sizes, and does not carry out the test on columns with a base below 30. You can change the minimum sample size if required, by entering a new value in the Minimum Base field in the Statistics tab. Multiple response variables. The test is invalid if the two rows being tested can have overlap (that is, one person can belong in both of them). However, there is no way that Survey Reporter can check for this. Two-tailed test. This is a two-tailed test, which means that it reports all significant differences between the proportions in all of the columns regardless of which row contains the greater proportions. Statistical Formula for the Paired Preference Test The paired preference element is usually specified as a row element to compare two rows for each column independently. However, you can specify it as a column element to compare two columns for each row independently. The following information assumes specification as a row. The following table shows the formulae used for conducting the paired preference test in IBM SPSS Data Collection Survey Reporter. Notation w o w 2 o e o =(w o ) 2 / w 2 o c i c j Description Sum of the weights for the column. Sum of the squared weights for the column. ffective base for the column. Sum of the weights for the cell in the i th row. Sum of the weights for the cell in the j th row.

248 234 Chapter 9 Notation p i = c i /w o p j = c j /w o Description Column proportion in the i th row. Column proportion in the j th row. Test Statistic Under the null hypothesis H o : p i = p j the paired preference test statistic is calculated using the following expression: The test is undefined if p i = p j =0orife o <2. Pvalues p values are computed using the t distribution with e o -1 degrees of freedom. References Kish, L (1965), Survey Sampling, New York: John Wiley and Sons. ISBN X. Product Difference Test The product difference test is not a separate statistical test in its own right. Instead, it enables you to apply statistical testing (using the column proportions or column means tests) to all combinations of categories in a number of variables. One use for this is to identify those attributes of tested products that show significant differences between products. The test creates a table specification by breaking down a number of variables, known as difference attributes, added to the side of the table, and creating a separate row for each category in each variable, and for each combination of categories from the variables. For example, if you use the variables education and biology as difference attributes, the test first creates one row for each category (for simplicity, these examples omit the Not Answered categories, but if you choose to include them the table will also include rows for those categories): education Yes education No biology Yes biology No If you request two combinations of difference attributes, it also creates a row for each combination of categories in the two variables to give the following rows: education Yes education No

249 235 Applying Statistical Tests biology Yes biology No education Yes biology Yes education Yes biology No education No biology Yes education No biology No Having created the side of the table, the test applies the column proportions and/or column means test to the table, using the columns in the variable specified on the top of the table. The test also hides any rows that do not contain significant results, and sorts the rows by significance. The end result is a table that displays a detailed breakdown of significant results by combination of categories. Adding an inner side variable You can further break down the analysis of the difference attributes by placing another variable (known as the inner variable) on the side of the table. Instead of creating one row for each single category and combination of categories, IBM SPSS Data Collection Survey Reporter creates a whole section. For example, you could add gender as the inner variable to give the following rows: education Yes gender Base education Yes gender Male education Yes gender Female education No gender Base education No gender Male education No gender Female biology Yes gender Base biology Yes gender Male biology Yes gender Female biology No gender Base biology No gender Male biology No gender Female education Yes biology Yes gender Base education Yes biology Yes gender Male education Yes biology Yes gender Female education Yes biology No gender Base education Yes biology No gender Male education Yes biology No gender Female education No biology Yes gender Base education No biology Yes gender Male education No biology Yes gender Female education No biology No gender Base education No biology No gender Male education No biology No gender Female Rows are also created for the base of the inner variable and for non-categorical items such as means. You can configurethetestsothatitdisplaysallresults, or only those results that are statistically significant.

250 236 Chapter 9 The statistical formulae for the test are as shown for the column proportions and the column means test. See Statistical Formula for the Column Proportions Test and Statistical Formula for the Column Means Test. xample of the Product Difference Test Sample Script File: ProductDifferenceTest.mrs The examples in this topic are based on the Museum sample data set. The product difference test in this example is based on a table with gender on the side of the table (the inner variable) and prefer on the top of the table. Three difference attributes are used: education, biology, andbefore. The test uses the three combinations option (though note that, in this case, the results are the same as for one combination; that is, no additional significant results are found using two and three combinations). ach category from each attribute variable is combined with each item in the side variable. The default settings are used so that the test applied is the column proportions test, with the default significance levels of 5% and 10%, and default minimum base and small base settings of 30 and 100 respectively. For information on how to set up the table and add the test, see Adding a Product Difference Test.

251 237 Applying Statistical Tests Figure 9-56 Product difference test on table of gender by prefer, difference attributes are education, biology, before The script begins by specifying the number of variables to combine on the side of the table (also known as difference attributes) inthenside variable. It also specifies the number of variable combinations to apply in the NCombs variable: Dim NSide, NCombs NSide = 3 NCombs = 3 In this case, three difference attribute variables will be used, and three combinations will also be used. This means that a row will be created for all combinations of each category in three variables. Note that when a combination value greater than 1 is used, lower combinations are also included, for example, in this case, one- and two- variable combinations are also created. The script then specifies a single top variable, a SideInner variable, which is an additional side variable that creates a further layer of combinations over and above those specified by the NCombs variable, and three SideVars, which identify the three variables to use as the difference attributes: Dim TopVar, SideInner, SideVars[20] TopVar = "prefer" SideInner = "gender" SideVars[0] = "education"

252 238 Chapter 9 SideVars[1] = "biology" SideVars[2] = "before" The script then adds an empty side axis variable called MainSide to the table, and creates a side elements collection: TableDoc.Tables.AddNew("T1", "axis({}) as MainSide * " + TopVar) Sidels = TableDoc.T1.Side.MainSide.lements Sidelno = 0 The script then builds up the side element specification using functions to create an element for each combination of categories in the selected SideVar variables. If a SideInner variable is specified, as in this example, each combination is further expanded by combining it with each category in the SideInner variable. The result is a side axis containing a row for each category combination. The cell items for the table are adjusted to include a column base cell item as the first item on the table. This is required because otherwise the base would not be visible on the finished table: TableDoc.T1.CellItems.Clear() TableDoc.T1.CellItems.AddNew(24, 0) TableDoc.T1.CellItems.AddNew(1, 1) A column proportions test is added to the table: Dim SigLev SigLev = 10.0 TableDoc.T1.Statistics.Add("ColumnProportions") TableDoc.T1.Statistics["ColumnProportions"].SigLevel = SigLev The script displays the minimum p value in a separate column on the table, and sorts the table in ascending order based on the value in this column: TableDoc.T1.Statistics.ShowMinPVal = True TableDoc.T1.SortColumn = TopVar + "{MinPVal}" TableDoc.T1.SortColumn.Order = 0 In addition, a hide rule suppresses any rows where the minimum p value is greater than a value equivalent to the significance level (siglevel/100). This has the effect of hiding any rows that are not significant at the selected level: Dim R Set R = TableDoc.T1.Rules.AddNew() R.Type = 0 ' hide R.Target = 0 ' row R.CellItemRef = 1 ' if cellitem 1 (1st non-base one) R.Operator = 4 ' is greater than R.Value = SigLev / ' siglevel / 100 R.lementRef = TopVar + "{MinPVal}" ' for MinPVal column R.IgnoreSpeciallements = False ' hide specials as well

253 239 Applying Statistical Tests Note that, as the table includes a base count in the first cell item position (position 0) the hide rule is based on the second cell item in the table (R.CellItemRef = 1). Details and Restrictions of the Product Difference Test Table Structure. The product difference test can be applied to tables that contain either no variables or a single variable on the side of the table, and a single variable on the top of the table. Statistical tests. The product difference test can be run using the column proportions and/or column means test. By default the column proportions test is used. Attribute combinations. You can use one, two, or three combinations of attributes. If a variable is present on the side of the table, this forms an additional combination, and is used as the inner nest variable; that is, the categories in this variable are changed first as the table rows are built up. Variable types. Only categorical variables can be used to form the table and the difference attributes. T-test Test The T-Test test is used to determine whether the mean of a numeric variable is significantly different from zero or some other specified value. The test may also be used to test for differences between means measured on matched samples (paired T-test), for example, between the means of two variables both obtained from the same sample of respondents. xamples can include trials of two drugs where the same person receives each drug at different times and observations are taken on their resulting condition after using each drug. The test might also be employed to study a comparison of a group of students competencies in two areas (verbal and mathematical, for example) by analyzing two sets of test results. The pairing of data must be taken into account as, for example, it is necessary to adjust for each particular patient s general reaction to treatments; similarly for each pupil s overall academic competence (students obtaining better marks in one test could be more likely to do well in the other). xample of the T-test Test Sample Script File: TTestTests.mrs This example script is based on themuseumsampledataset. The T-test test in this example determines whether: The number of visits in the last twelve months is significantly different from zero for each category in age. The total number of visits is significantly different from six for each category in age.

254 240 Chapter 9 The difference in numeric rating values for dinosaurs and mammals is significantly different from zero for each category in age. The entrance rating for fossils is significantly different from zero, once the factors have been reset from (1 to 5) to (-2 to 2), for each category in age. The first test determines if the number of visits in the last twelve months is significantly different from zero for each category in age. The second test determines if the total number of visits is significantly different from six for each category in age. The third test determines if the difference in numeric rating values for dinosaurs and mammals is significantly different from zero for each category in age. The fourth test determines if the entrance rating for fossils is significantly different from zero, once the factors have been reset from (1 to 5) to (-2 to 2), for each category in age. Details and Restrictions of the T-test Test T-test usage The T-test test is not suitable for all tables. The value of T will be zero if there is no difference in the data. The simplest use of the one-sample T-test is when testing whether the mean of a variable already coded in columns of the data is zero. There may be occasions when you want to use a one-sample T-test on values that are not the same as those in the data. To test whether a mean may be different from a non-zero value, subtract that value from each data value. In other words, to test whether the mean number of visits to a supermarket is equal to 2, you actually test whether the mean of (number of visits to supermarket 2) is equal to 0. To make a paired test between two data values, test whether the difference between them is zero. Statistical Formula for the T-test Test The following table shows the notation used in this topic. In the formulae for axis-level test statistics, the formula is applied separately to the counts in each column or row, according to whether the axis containing the stat= option is the row or column axis. Notation Description The number of basic count elements in the axis or segment. The (weighted) count in the ith cell of a row or column representing that axis.

255 241 Applying Statistical Tests Notation Description The (weighted) base of the row or column. The unweighted base of the row or column. Sum of factors Mean Standard deviation Standard error of mean One-sample and paired T-Test is tested against Student s t-distribution with N - 1 degrees of freedom. Adding a Statistical Test You can apply a number of statistical tests to your tables to check the statistical significance of your results.

256 242 Chapter 9 To add a statistical test In the Tables pane, select the table to which you want to apply the test. Note that most of the statistical tests are valid only for certain types of table; ensure that your tables meet the restrictions for your chosen test. See the Details and Restrictions topic for the appropriate test. If you are applying a paired preference test or a net difference test to a table, the process is slightly different from that for other statistical tests, as you also need to add a row or column to the table to contain the results. Before carrying out the remainder of these steps, you need to carry out the steps in Adding a Paired Preference Test or a Net Difference Test. From the menu bar, choose: Tables > Properties Choose the Statistics tab. Select the statistical test that you want to apply to the table. If required, change the significance level(s) and the minimum and small base values. Choose OK. Generate the table: Figure 9-57 Generate table icon Sorting by Column Significance You can apply all of the following steps to a table in a single action, using the Sort by Column Significance option: add a column proportions and column means test to the table with the default significance level (5) add a minimum p value column to the table sort rows in ascending order by the minimum p value column hide rows where the minimum p value is greater than the significance level (greater than 0.05). If required, you can change any of these settings individually (for example, if you want to remove the hide option or change the significance level) using the relevant tabs on the Table Properties dialog box. To sort a table by column significance In the Tables pane, select the table to which you want to apply the test. From the menu, choose Tables > Sort by Column Significance

257 243 Applying Statistical Tests or choose the Sort by Column Significance button: Figure 9-58 Sort by Column Significance button The changes are applied to the table. Generate the table to see the results: Figure 9-59 Generate Table button Note that if there are no significant results, an empty table will be displayed. For more information, see the topic p Values on p Adding a Paired Preference Test or a Net Difference Test If you are applying a paired preference test or a net difference test to a table, the process is slightly different from that for other statistical tests, as you also need to add a row or column to the table to contain the results. To add a paired preference or net difference test In the Tables pane, select the table to which you want to apply the test. On the table, select the variable on which you want to run the test. Note: In the case of the Net difference test, this must be on the top of the table; for the paired preference test it can be either on the top or on the side. From the menu, choose: Variables > dit Table Variable On the dit Table Variable window menu, choose: Categories > Insert Categories or choose the Insert button: Figure 9-60 Insert button The Variable dit - Insert dialog box appears. This contains a list of all the items that you can add to a variable. In this case, you need to add either a paired preference or a net difference item, depending on the type of test you want to run. Select the item in the Available Items list and choose the >> button to move it to the Items to insert list. Choose OK to close the dialog box.

258 244 Chapter 9 In the dit Table Variable window, ensure that the new item is at the bottom of the list of categories, using the move down button: Figure 9-61 Move down button Use the Save and Close button to save your changes and close the dit Table Variable dialog box. Now add the test to the table. For more information, see the topic Adding a Statistical Test on p Adding a Product Difference Test You can add a product difference test to a table containing a column proportions or a column means test, to break down the results by category using a number of different variables, known as difference attributes. This enables you to see which combinations of categories produce significant results. For more information, see the topic Product Difference Test on p To add a product difference test Create a table with either no variables or one variable on the side and one variable on the top. Note: You can use an edited variable provided that you edit the variable before you specify the product difference test. Once you have specified a product difference test for a table, the entire table specification is frozen and any further edits that you make to variables will not be reflected in the table. In the Variables pane, use Shift+click or Ctrl+click to select the variables you want to use as the difference attributes. From the menu, choose: Tables > Add Difference Attributes The Difference Attributes dialog box appears. Choose the number of combinations to use: If you select one combination, each category in each of the difference attributes will be combined with each category in the variable on thesideofthetabletoformaseparaterowof the table. ach row will be tested for significance. ach row therefore contains a combination of two categories. If you select two combinations, in addition to the rows produced by the above set of combinations, a row is created for each combination of categories in all combinations of two difference attributes and the side variable. ach of these rows contains a combination of three categories. If you select three combinations, in addition to the 1-and 2-combination rows, a row is created for each combination of categories in all combinations of three difference attributes and the side variable. ach of these rows contains a combination of four categories.

259 245 Applying Statistical Tests Note: Depending on the numbers of categories in each of your variables, this can result in a very large table, which may take a long time to generate and which may not contain any significant results unless your survey data contains a sufficiently large set of responses. By default, the column proportions test will be applied to the table. If you want to change this, deselect the Apply default statistics (column proportions) check box. By default, only significant results are displayed in the table. If you want to see all results, deselect the Apply default hide rules check box. Choose OK to close the Difference Attributes dialog box. On the Design pane, the table specification is now frozen, and the size of the table appears as Difference_Attributes_axis, representing the combinations of categories from the side variable and the difference attributes that you selected. If you deselected the default statistics check box, you must also select the statistical test you want to include using the Table Properties dialog box. From the menu, choose: Tables > Properties and select the appropriate options in the Statistics tab. You must then reselect the Difference Attributes dialog box and choose OK. Generate the table: Figure 9-62 Generate table button Note: If you do not see any results, this may be because your survey data contains insufficient records to support the number of attributes you have selected. Alternatively, it may be that none of the results is significant. Try selecting fewer attributes, or setting a lower significance level. Add Difference Attributes Use the Add Difference Attributes dialog box to specify the settings required to create a product difference test. To open the Add Difference Attributes dialog box: Create a table with either no variables or a single, non-grid variable on the side and a single, non-grid variable on the top. In the Variables pane, use Shift+click or Ctrl+click to select the variables you want to use as the difference attributes. From the menu, choose: Tables > Add Difference Attributes Fields on the Add Difference Attributes dialog box Difference attributes. Lists the variables that you have selected in the Variables pane. To change the difference attributes, press Cancel to return to the Variables pane.

260 246 Chapter 9 Number of combinations. Select the number of combinations of attributes that you want to test. For more information, see the topic xample of the Product Difference Test on p Apply default statistics (column proportions). By default, the column proportions test will be applied to the table with a significance level of 10%. If you want to change this, deselect the Apply default statistics (column proportions) check box, then use the Statistics tab of the Table Properties dialog box to set the required statistical test and significance level. Apply default hide rules. By default, results that are not significant at the selected significance level are not displayed in the table. If you want to see all results, deselect this box. Displaying Detailed Statistical Output You can display detailed diagnostics information about the statistical tests in a popup box. For more information, see the topic Diagnostics Information on p To display detailed statistical output Apply a statistical test to your table(s). For more information, see the topic Adding a Statistical Test on p From the menu, choose File > Properties In the Advanced tab, check the Generate detailed statistical output box, and choose OK. Generate the table(s): Figure 9-63 Generate table icon From the menu, choose Tools > View Detailed Statistical Output Details of the output are displayed in a popup box. Diagnostics Information When you run a statistical test on a table, you can optionally write out IBM SPSS Data Collection Survey Reporter diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The diagnostics file contains information for each table that contains a statistical test. The first line of the section describes the table, whether there is overlap in the columns tested, whether the table is weighted or unweighted, and whether the effective base was used. This is followed by additional information for each test.

261 247 Applying Statistical Tests The first column indicates the type of test: CHI. The chi-square test and/or Fisher s exact test. CPT. The column proportions test. CMN. The column means test. NTP. The net difference test for a category row. NTM. The net difference test for a mean row. PPT. The paired preference test. The remaining information is different for each test. For details of how to view diagnostics information, see Displaying Detailed Statistical Output. Diagnostics Information: Chi-Square Test When you run a statistical test on a table, IBM SPSS Data Collection Survey Reporter can create diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The information varies according to the test. Here is the information for the chi-square test example: Figure 9-64 Diagnostics information for chi-square test example formula. Displays the name of the formula used. rows/cols. These indicate the category rows and columns that the test was performed on. chisqd. The chi-square value. chidof. The degrees of freedom. pval. The p value. The above example uses the Pearson test. When the Yates correction is used, the following columns are also present: absterm. The absolute value of the product of one diagonal minus the product of the other diagonal. When the absterm value is less than the halfsum value, the Yates value is not calculated and the chi-square value is set to zero. halfsum. Half the sum of frequencies in all the cells. fisher2. The two-tailed probability of chi-square as calculated by Fisher s exact test. fisher1. The one-tailed probability of chi-square as calculated by Fisher s exact test.

262 248 Chapter 9 Diagnostics Information: Cell Chi-Square Test When you run a statistical test on a table, IBM SPSS Data Collection Survey Reporter can create diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The information varies according to the test. Here is the information for the : Figure 9-65 Diagnostics information for cell chi-square test example The above example uses the Pearson test with the Yates correction (when required). Note that the diagnostic information for the cell chi-square test includes information for every table cell. formula. Displays the name of the formula used. rows/cols. These indicate the category row and column that the test was performed on. chisqd. The chi-square value. chidof. The degrees of freedom. pval. The p value.

263 249 Applying Statistical Tests siglevel. The significance level. sample. The sample size. Diagnostics Information: Column Proportions Test When you run a statistical test on a table, IBM SPSS Data Collection Survey Reporter can create diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The information varies according to the test. Here is the information for the first column proportions test example: Figure 9-66 Diagnostics information for column proportions test example row/cols. This is in the form nxy, where n represents the category row (the first category row is 1, the second category row is 2, etc.) and x and y are the IDs of the pair of columns. pval. The p value. tval. The t value. dof. The degrees of freedom. se. The standard error. sig. The significance level chosen for the test. p1, p2. The proportions in the two columns. r1, r2. The counts in the two cells. If the table is weighted, these are weighted. w1, w2. The bases in the two columns. If the table is weighted, these are weighted. e1, e2. Theeffectivebaseinthetwocolumns. Thesearethesameasthebasesiftheeffective base option was not used.

264 250 Chapter 9 Diagnostics Information: Column Means Test When you run a statistical test on a table, IBM SPSS Data Collection Survey Reporter can create diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The information varies according to the test. Here is the information for the column means test example: Figure 9-67 Diagnostics information for column means test example row/cols. This is in the form nxy, where n represents the category row (the first category row is 1, the second category row is 2, etc.) and x and y are the IDs of the pair of columns. pval. The p value. tval. The t value. dof. The degrees of freedom. se. The standard error. sig. The significance level chosen for the test. m1, m2. The means in the two columns. xx1, xx2. The weighted sum of squared values in each column (Y i ). x1, x2. The weighted sum of values in each column (X i ). n1, n2. The weighted count of cases in the mean row in each column (w i ). e1, e2. Theeffectivebaseinthetwocolumns. Thesearethesameasthebasesiftheeffective base option was not used. Diagnostics Information: Net Difference Test When you run a statistical test on a table, IBM SPSS Data Collection Survey Reporter can create diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The information varies according to the test. Here is the information for the Net difference test example: row/cols. This is in the form n/(3-4)-(1-2), wheren represents the category row (the first category row is 1, the second category row is 2, etc.) and 1, 2, 3, and4 are the IDs of the four columns. pval. The p value. tval. The t value. dof. The degrees of freedom. se. The standard error.

265 251 Applying Statistical Tests sig. The significance level chosen for the test. eb. The effective base for the column. p1, p2, p3, p4. The proportion in columns 1, 2, 3, and 4. r1, r2, r3, r4. The counts in columns 1, 2, 3, and 4. w1, w2, w3, w4. The sum of weights (weighted base) for columns 1, 2, 3, and 4. e1,e2,e3,e4.the effective base in columns 1, 2, 3, and 4. Diagnostics Information: Paired Preference Test When you run a statistical test on a table, IBM SPSS Data Collection Survey Reporter can create diagnostics information that shows the p values and some of the intermediate figures used to calculate the statistics. The information is in comma-delimited format, so you can open it in Microsoft xcel and perform calculations on the data. The information varies according to the test. Here is the information for the paired preference test example: Figure 9-68 Diagnostics information for the paired preference test The paired preference test in the above example is specified as a row in the test on Table2 and as a column in the test on Table3. The following information assumes specification as a row.

266 252 Chapter 9 rows/col. This is in the form a + b / c, wherea and b are the rows being tested, numbered starting from 0, corresponding to those displayed in the table, and c is the column being tested, numbered starting from 0, corresponding to those displayed in the table. pval. The p value. tval. The t value. denom. The denominator of the t value. sig. The significance level selected for the test. n. The count in the base row for the column. If the table is weighted, this is weighted. eb. The effective base for the column. p1, p2. Theproportioninrows1and2. r1, r2. The counts in the two cells. p Values The p (probability) value is the basis for deciding whether or not there is a relationship between the data being tested. Generally you start with the null hypothesis, which is the assumption that there is no relationship between the data. If the p value is small enough (usually less than 0.05 or 0.01), you can reject the assumption of no relationship and conclude that there is a relationship. Afulllistofthep values for each pair of columns tested in each row is available in the diagnostics information file for the table. See Diagnostics Information for further details. IBM SPSS Data Collection Survey Reporter reports p values as a decimal value with six decimal places (although trailing zeroes after the decimal symbol are not displayed by default when you open the file in Microsoft xcel). A reported p value of 0.05 is equal to a significance level of 5%. If the p value is smaller than the significance level you select for the test, the test statistic is significant. The p value is also called the observed significance level. Figure 9-69 p values for the column proportions test example

267 253 Applying Statistical Tests This example shows the p values for the first column proportions test example. It shows the row/cols and pval columns from the diagnostics data with the addition of the row labels. In the example, the column proportions test was run at the 5% significance level, and one row Human biology wasfoundtobesignificant. Notice that the p value in this row is This is the only row with a p value of less than Displaying p values Afulllistofthep values for each pair of columns tested in each row is available in the diagnostics information file for the table. See Diagnostics Information for further details. Displaying minimum p values on a table If you add a column proportions or column means test to a table, you can optionally display on the table a column showing the smallest p value found for any of the pairs of columns tested in each row of the test: From the menu, choose Tables > Properties In the Statistics tab of the Table Properties dialog box, check the test Column proportions or Column means check box. Check the Show minimum p-value box. This adds a new column with the name Minimum Pval to the table. ach row of this column displays the lowest p value found for any pair of columns tested in the row. If the table has more than two columns, the column IDs for the pair of columns that generated the lowest p value are also displayed. Note: The minimum p value column is not valid, and so is not displayed, on a table with any nesting or concatenation on the top of the table. Sorting a table by minimum p values If you have added a minimum p value column to a column proportions or column means test, you can sort the table on this column, so that the most significant rows appear at the beginning of the table: From the menu, choose Tables > Properties In the Sort tab of the Table Properties dialog box, select the variablename{minimum Pval} option from the Sort rows based on drop-down. Choose the ascending order option button.

268 254 Chapter 9 Hiding non-significant rows If you have added a minimum p value column to a column proportions or column means test, you can hide rows based on the value in this column. This means that you can carry out a test on all the rows in the table and then hide any rows that contain no significant results, as determined by the minimum p value: From the menu, choose Tables > Properties In the Hide tab of the Table Properties dialog box, check the Hide rows box. In the drop-down list, select greater than. In the numeric field to the right of the list, enter the significance level expressed as a percentage; for example, if you are using a significance level of 5, enter In the based on drop-down list, select the variablename{minpval} option. Sorting by Column Significance Survey Reporter includes a menu option that enables you to apply all of the above changes to a table in a single step. The Sort by Column Significance option carries out the following actions on the selected table(s): adds a column proportions and column means test to the table with the default significance level (5) adds a minimum p value column to the table sorts rows in ascending order by the minimum p value column hides rows where the minimum p value is greater than the significance level (greater than 0.05). If required, you can change any of these settings (for example, if you want to remove the hide option or change the significance level) using the relevant tabs on the Table Properties dialog box. See Sorting by Column Significance for further information. Weighted Data and the ffective Base When you run statistical tests on weighted tables, the test is always run on the weighted counts. If you want to run the tests on the unweighted data, you must first remove the weighting. When the table is weighted, you can optionally use a special base called the effective base. This option is selected by default. The effective base is designed to reduce the likelihood of the statistical tests producing significant results because of the adjustments made by weighting; the effective base takes these adjustments into account. The effective base is also a test of how good the weighting is. If the weighting is inflating the answers from a particular group by a large factor, the effective base tends to be much smaller than both the unweighted and the weighted base. The closer the effective base is to the unweighted base, the better the weighting is.

269 255 Applying Statistical Tests The effective base is calculated by dividing the squared sum of weights for all of the respondents in the weighting matrix table by the sum of the squared weights. The option to use the effective base is selected by default. You turn it off by deselecting the Use ffective Base option on the Statistics tab of the Table Properties dialog box. You can display the effective base on a table by adding an ffectivebase element to a variable s axis expression. For example: age{base(), effectivebase(),..} You cannot directly enter an expression on the effective base. The calculation of the effective base is based on the preceding base and uses any expression attached to the base. For example, in this axis expression the effective base includes only male respondents, as specified in the base expression: age{base('gender={male}'), effectivebase(),..} Reference For an article that describes some methods of adjusting the base to take into account weighting, see Potthoff R., WoodBury M., Manton G. (1992). quivalent Sample Size and quivalent Degrees of Freedom Refinements for Inference Using Survey Weights Under Superpopulation Models, Journal of American Statistical Association, V87, This article has an equivalent sample size (formula 1.6) that is the same as the effective base. Displaying an ffective Base on a Weighted Table This example is based on the Museum sample data set. museums{effectivebase(),..northern_gallery}

270 256 Chapter 9 Figure 9-70 Weighted table with column proportions test and effective base Overlapping Data Most of the statistical tests are based on standard t tests that assume that the two samples being compared are independent of each other. When the columns of a table are formed from the categories of a multiple response variable, data from the same case can be present in both of the columns being tested. This is known as overlapping data, and it means that the two samples cannot be considered independent. For example, the multiple response variable museums is based on the following question, for which respondents can select any number of responses. When this variable is on the top of a table, respondents who selected more than one response appear in more than one column. Figure 9-71 Museums question: Which museums or art galleries have you visited or do you intend to visit? When the columns of a table are formed from the categories of a single response variable, the data in the columns are mutually exclusive, although this does not necessarily guarantee that they are independent.

271 257 Applying Statistical Tests IBM SPSS Data Collection Survey Reporter can perform the column proportions and column means tests on overlapping data because it can detect overlapping data in the columns being tested and use a formula to compensate for the fact that some cases appear in more than one column. The chi-square test cannot be performed on overlapping data. For more on the theory of overlapping samples, see Kish, Survey Sampling. (Kish,L.Survey Sampling. New York: John Wiley and Sons. ISBN X.) Hierarchical Data All of the statistical tests are based on the assumption that the samples being compared are independent of each other. However, in hierarchical data, there is normally a relationship between the lower levels and the higher levels, which means that cases at the lower level are not independent of each other. For example, you would not expect the voting patterns of the members of a household to be totally independent of each other, nor would you expect the various journeys or shopping trips made by an individual to be unrelated to each other. These relationships mean that the underlying assumptions required for the statistical tests are almost never satisfied when you run the tests on lower level data. Therefore, when you are working with hierarchical data, IBM SPSS Data Collection Survey Reporter changes the specified table level (a warning message is not provided) if any of the variables included in the table are from a lower level. Selecting Columns to Test For the column proportions and column means tests, by default columns are tested in groups that are determined by the structure of the table. For example, in a table with three categories in the column variable, columns would be labeled A, B, and C, and the test would be carried out on all combinations of columns A-C. In nested tables, the columns of the inner nest level are repeated (and given unique IDs), and the test is carried out for each set of columns within the nesting level. You can select the columns you want to test against each other using the For more information, see the topic Column Test in Chapter 15 on p. 340.Column Test button in the Statistics tab of the Table Properties dialog box. All combinations of the columns that you specify are tested. Separate the column IDs using a forward slash character, for example: "A/B/C" This tests all combinations of columns A, B, and C. You can specify separate groupings of columns to test by separating groups of columns with a comma, for example: "A/C/, B/D/F" This tests all combinations of columns A, C, and, and all combinations of columns B, D, and F.

272 258 Chapter 9 Columns that you do not include are omitted from the tests. If you do not specify columns to test, the default column groupings are used. Note: If you specify columns to test, ensure that the column IDs you specify exist in the table, and that they correspond to valid combinations of columns to test. You can check this by running the test first using the same table specification but with the default column selection. ColumnsID property Starting with IBM SPSS Data Collection Base Professional 5.6 you can define column IDs as a string using the ColumnsID property. ach character in the string is used to allocate a column ID, with a period or space character used to indicate that an ID should not be allocated. A character needs to be added to the ID s string for each column, even if the column is hidden. When allocating column IDs a character should also be added for the base columns. For the table below, the column IDs could be set as follows to test Yes-Male against No-Male, and Yes-Female against No-Female: Table.Statistics.ColumnIDs = "...MF.NG" Table.Statistics.TestColumns = "M/N, F/G" Figure 9-72 Column Proportions Test with New Column IDs Note: Column IDs are only applied to visible table elements. Hidden elements are not taken in consideration when defining a Column IDs as a string. Setting the Significance Levels By default, the column proportions, column mean, net difference test, and paired preference tests are run at the 5% significance level. However, you can optionally run a test at another significance level, such as the 10% or 1% significance level. You can also run the test at two significance levels on the same table. In the resulting table, the IDs of columns that are significant at the higher level appear in upper case, and those that are significant at the lower level appear in lower case.

273 Minimum Base and Small Base Values in Statistical Tests 259 Applying Statistical Tests By default, when you carry out a column proportions, column mean, net difference test, or paired preference test, if a table includes a base value that is below the recommended minimum base of 30, the test is not carried out. This is denoted by two asterisks (**), which are placed on the table instead of the result. If a table includes a base value that is above the minimum base but below a small base value of 100, the test is carried out, but a single asterisk (*) next to the test denotes that the base value is small. The annotations also indicate this. You can change the default minimum base and small base values if required, by entering new values in the Minimum Base and Small Base fields in the Statistics tab of the Table Properties dialog box.

274 Applying Weighting Chapter 10 Weighting is another term for sample balancing. During a survey, it is not possible to interview everyone, so only a sample of the population is interviewed. If this sample group does not accurately reflect the proportions of various groups in the total population, you can weight the survey results. For example, of the 602 respondents interviewed in the Museum survey, 56.31% were male and 43.69% were female, which does not reflect the proportions of males and females in the general population. However, by using the genbalance weighting variable to weight the tables, you can inflate the responses from the female respondents and deflate the responses from the male respondents to reflect the actual balance of the genders. How table weighting works When IBM SPSS Data Collection Survey Reporter calculates counts in an unweighted table (or unweighted counts in a weighted table), it increments the count in each cell by 1 each time it finds a case that satisfies the conditions that define the cell. However, when Survey Reporter calculates counts in a table weighted with the genbalance weighting variable, it increments the counts in each cell as follows: By 1.14; that is, (1 * 50/43.69) for female respondents By 0.89; that is, (1 * 50/56.31) for male respondents This assumes that the male/female proportions required are 50% of each. The genbalance variable is simply a variable that stores the value 1.14 for every female and 0.89 for every male. Weighting variables must be numeric variables. However, not all numeric variables are suitable for use as weights. Generally, weighting variables are created specially, typically using IBM SPSS Data Collection Base Professional. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

275 261 Applying Weighting Weighting hierarchical data When you are using a hierarchical view of the data, the level of the weighting variable restricts the levels at which you can generate the table: you cannot generate a table at a level that is higher than the level of the weighting variable. To illustrate this, consider a survey similar to the Household sample, which has the following levels structure: Figure 10-1 Household structure If the weighting variable is at the household (top) level, you can generate the table at the household, person, trip, or vehicle level (assuming the other variables on the table do not restrict the available levels). If the weighting variable is at the person level, you cannot generate the table at the household level, because it is higher than the level of the weighting variable and you cannot generate the table at the vehicle level because it is at a parallel level to the weighting variable. However, you can generate the table at the trip level, because it is lower than the level of the weighting variable. For more information, see the topic xamples Showing Results Generated at Different Levels in Chapter 11 on p Showing the Unweighted Base in Weighted Tables When working with weighted data, it is good practice to show the unweighted base values in your tables as well as the weighted base values. This is particularly important when showing percentages. By default, IBM SPSS Data Collection Survey Reporter automatically adds an unweighted base at the start of each variable in a weighted table. For an example of a weighted table containing unweighted bases, see Counts and Unweighted Counts. The unweighted base shows the total number of cases in the variable before any weighting has been applied. Only one value is ever shown in the table cells formed from the unweighted base, even when there are multiple cell contents. The value that is shown is the unweighted base count, regardless of what cell contents have been requested for the table. You can stop the automatic insertion of the unweighted bases by deselecting the Add an unweighted base option on the Weight tab of the Table Properties dialog box. However, to comply with good practice guidelines, ensure that the unweighted base is shown when necessary. Adding Weighting to a Table You can apply weighting to a selected table or to all tables in the table document. When you generate tables that use weighting, the variable used for weighting is shown in the right header in the Results tab.

276 262 Chapter 10 To apply weighting Select the table(s) to which you want to add weighting. From the menu, choose Tables > Properties Choose the Weight tab. By default, all variables that have been set up for use as weighting variables are available in the drop-down list. However, you can use any numeric variable in the table document to use as a weighting variable. Ifyouwanttouseanon-weighting variable, check the Show all numeric variables box below the drop-down list to see the full list of available variables. Select a variable from the list. To apply the weighting to the selected table(s) only, choose OK. To set the weighting as the default for all new tables that you create, choose Set as Default, then choose OK. Overriding Table Weighting You can override the table weighting for specific rows or columns so that they use a different weighting variable, or so that they are unweighted. This is an advanced feature that uses variable editing to change the weighting properties for categories in a variable. These instructions assume that you want to override the weighting for a specific category in a variable, on every table where the variable appears in the table document. To apply the changes to the variable for a single table, select the variable on the table definition area in the Design pane and use the dit Table Variable option on the menu. To change the weighting for a row or column Select the variable in the Variables pane. From the menu, choose Variables > dit Variable In the list of categories that make up the variable, select the category you want to edit. From the dit Variable dialog box menu, choose View > View Properties or choose the View Properties button on the toolbar. The Properties pane appears. This lists all the properties that you can change for the selected category. The drop-down list beside the Override table weight using: property contains a list of all the variables that you can use to override the table weight. Select a variable from the drop-down list. If you want the category to be unweighted, select No weight from the list.

277 263 Applying Weighting Repeat for any other categories in the variable that you want to change, then choose Save and Close from the toolbar to save your changes. Add the variable to a table, or regenerate existing tables that use the variable, to update the weighting.

278 Tabulating Hierarchical Data Chapter 11 Surveys and questionnaires often contain individual questions and sets of questions that are asked more than once. For example, questionnaires often contain grid questions that ask respondents to choose a rating on a predefined scale for a number of products in a list, and sets of questions that respondents are asked to answer for each product in a list of products or for each person in a household. The data collected using these types of constructions is sometimes referred to as hierarchical data. The topic on Loops and Grids in the Using Variables section gives an introduction to hierarchical survey structures. This section contains additional information about how to work with hierarchical data in IBM SPSS Data Collection Survey Reporter, and also provides information about working with grid and loop slices when you are using the flat view. All examples in this section use the Household XML Sample data set. For more information, see the topic The Household Sample on p The Hierarchical View and the Flat View The IBM SPSS Data Collection Data Model has two ways of representing the case data: Using a hierarchical view (sometimes called HDATA). Using a flat view (sometimes called VDATA). The Hierarchical View In most cases, IBM SPSS Data Collection Survey Reporter displays a hierarchical view of the data. This means that: The Variables pane displays hierarchical variables (such as grids and loops) as expandable items. You can create grid tables. You can use variables that are nested inside a loop or grid in your tables. You can choose the generation level for your tables. You can include slices of expanded loops and grids in your tables. When you create a filter, you need to specify a level. It is generally preferable to use the hierarchical view whenever possible, because it enables you to create grid tables and provides better support for tabulating data collected using loops. Moreover, some hierarchical data cannot be represented in the flat view. For example, data collected using an unbounded loop cannot be flattened, because the maximum number of iterations is unknown. A lower level in a IBM SPSS Quanvert levels project is a typical example of an unbounded loop. The flat view is therefore unsuitable for this type of data. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

279 265 Tabulating Hierarchical Data The Flat View In some cases, Survey Reporter displays a flat view of the data. This means that grids and loops are shown as expandable items in the Variables pane, but you cannot create a grid table, or place on a table a variable that is inside a loop or grid. However, you can use a slice of a grid or loop in a table. Moreover, because the data is flat, you do not need to worry about levels when you are generating tables or creating filters. Changing the View Note that if you want to change the view, you must do so before you start defining your tables and filters. If you have already started defining tables or filters, you will need to start a new table document before you change the view. To see which view of the data is in use From the menu, choose File > Properties Choose the Advanced tab. The Data view drop-down list displays the view of the data (Hierarchical or Flat) that is being used. To change the view If necessary, save the existing table document and then start a new one. From the menu, choose File > Properties Choose the Advanced tab. Select the required view from the Data view drop-down list. Click OK. Using The Variables Pane with Hierarchical Data This topic describes working in the Variables pane when you are using the hierarchical view of the data. Note that when you are using the flat view, although grids and loops are shown as expandable items, you cannot create a grid table, or use a variable that is inside a loop or grid in a table as described in this topic. However, you can use a slice of a grid or expanded loop in a table. The Variables pane represents loops and grids as expandable items. Click the grid or loop to expand it. This reveals the variables that are contained within the loop or grid.

280 266 Chapter 11 Figure 11-1 The Variables pane You can use the variables inside the loops and grids in your tables, in the normal way. You can also generate your tables at different levels. For information on the significance of generating your tables at different levels, see xamples Showing Results Generated at Different Levels You can use grids and loops that are defined as expanded to create grid tables. The person loop in the example above is an expanded loop, and the vehicle loop contains a grid called rating. When you look at the variables inside an expanded loop or a grid, you can see the iterations. Figure 11-2 The Variables pane, expanded For more information, see the topic Understanding Grid Tables on p The iterations are sometimes called grid or loop slices and you can use them in your tables. For more information, see the topic Tabulating Grid and Loop Slices on p The iterations are not shown for loops that are unbounded.

281 267 Tabulating Hierarchical Data Note: Compounds and blocks are used to group questions for display or convenience only and do not define a true hierarchical structure. Therefore, you cannot use compounds and blocks to create grid tables. However, you can use the variables that are nested within a compound or blockinyourtablesinthenormalway. Setting the Table Generation Level When you use the hierarchical view of the data, generating tables can take place at different hierarchical levels. For more information, see the topic xamples Showing Results Generated at Different Levels on p To set the table generation level In the Tables pane, select the table for which you want to change the level. From the menu, choose Tables > Properties Choose the Level tab. The Level drop-down list contains a list of all levels at which results can be generated for the current table. Select the level you want to use, then choose OK to close the dialog box. Generate the table: Figure 11-3 Generate table button xamples Showing Results Generated at Different Levels When you use the hierarchical view of the data, you can define the level at which each table is generated. The level that you choose affects the figures that are shown in the cells of the table. The level you use to generate your results will depend on the level of detail you are interested in. For example, in the Household sample data set, when you generate a table at the top level, each case corresponds to a household and therefore the counts show numbers of households; when you generate the table at the person level, each case corresponds to a person and therefore the counts show numbers of people; when you generate a table at the trip level, each case is an overseas trip and the counts show numbers of trips, etc. This topic uses the Household sample data set to illustrate how data is generated at different levels. For details of the structure of the Household sample, see The Household Sample.

282 268 Chapter 11 Notes on generating the tables All tables in this topic have a single cell item, Counts, and are set up to hide rows and columns where the base count is zero. (to change these properties, press F4 to display the Table Properties tab and set the properties in the Cell Contents and Hide tabs). Table 1: Top-level variables tabulated at the top level The first table crosstabulates two top-level variables (housetype and region) and generates results at the top level. The counts in the cells refer to households because in this survey the top-level questions refer to households. To create this table, add the housetype variable to the side of the table and the region variable to the top. Use the default level setting (Top). Figure 11-4 Top-level variables tabulated at the top level The cell in the top left corner of the table shows that there are 10 households in the sample. Table 2: Person-level variables tabulated at the person level This table crosstabulates two person-level variables (occupation and gender) and results are generated at the person level. ach cell shows the number of people of a given occupation and gender. To create this table, expand the Person loop and then add the occupation variable to the side of the table and the gender variable to the top. Use the person level setting.

283 269 Tabulating Hierarchical Data Figure 11-5 Person-level variables tabulated at the person level Looking at the top left cell, we can see that there are 25 cases at the person level, or, to put it another way, there are 25 people in the sample. Table 3: Person-level variables tabulated at the top level This table crosstabulates the same two person-level variables, but this time the results are generated at the top level. This means that instead of showing the number of people of a given occupation and gender, each cell now shows the number of households that contain people of the given occupation and gender. To create this table, use the same structure as for the previous table, but this time change the level to the household (Top) level. To change the level, press F4 to display the Table Properties tab and choose the Level tab. Select Top from the drop-down list box. Figure 11-6 Person-level variables tabulated at the top level Looking at the top left cell, we can see that the base for the table is the same as in the first table shown above. This is what you would expect because both tables are counting the number of households and are unfiltered, and every household contains at least one person.

284 270 Chapter 11 Table 4: Trip-level variables tabulated at the trip level The next table crosstabulates two trip-level variables (country and purpose) and results are generated at the trip level. This means that each cell shows the number of overseas trips that involved a particular country and purpose. To create this table, expand the Trip loop (which is inside the Person loop) and then add the country variable to the side of the table and the purpose variable to the top of the table. Use the default Level setting. Figure 11-7 Trip-level variables tabulated at the Trip level Looking at the top left cell, we can see that there were a total of 24 overseas trips (or to put it another way, there are 24 cases at the trip level). Table 5: Trip-level variables tabulated at the person level The next table crosstabulates the same two trip-level variables, but this time the results are generated at the person level. This means that instead of showing the number of overseas trips that involved a particular country and purpose, each cell now shows the number of people who took trips that involved a particular country and purpose. To create this table, use the same table structure as in the previous example, but this time change the level to person.

285 271 Tabulating Hierarchical Data Figure 11-8 Trip-level variables tabulated at the Person level Looking at the top left cell, we can see that the base for the table is 12. This is lower than the base in the Table 2 above (which tabulates two person-level variables at the person level) because some people did not take an overseas trip and therefore there are no records (cases) at the trip level for those people. Table 6: Variables from different levels tabulated at the default level You can create tables that use variables from more than one level. The next table crosstabulates a person-level variable (gender) with a trip-level variable (purpose). When you use variables from parent and child levels like this, the generation level defaults to the level of the lowest-level variable, which is the trip level in this example. This means that each cell in this table shows the number of overseas trips for a particular purpose and the gender of the person who took them. To create this table, expand the Person loop and add the gender variable to the side of the table and then expand the Trip loop and add the purpose variable to the top. Figure 11-9 Variables from different levels tabulated at the default level If you look at the Base column, you can see that of the 24 overseas trips that were taken, 11 were takenbymalesand13byfemales.

286 272 Chapter 11 Note that the base for the table (24) is the same as the base in Table 4 above (which tabulates two trip-level variables at the trip level). Table 7: Variables from different levels tabulated at a higher level The next table crosstabulates the same person-level variable (gender) with the same trip-level variable (purpose). However, this time the results are generated at the person level. This means that instead of showing the number of overseas trips, each cell now shows the number of people of each gender who took trips that involved a particular purpose. To create this table, use the same table structure as in the previous example, but this time change the level to person. Figure Variables from different levels tabulated at a higher level If we look at the Base column, we can see that of the 12 people who took overseas trips, 6 were males and 6 were females. The top left cell shows that the base for the table is 12, which corresponds with the base in the fifth table shown above, which tabulates two trip-level variables at the person level. Note that the base counts every person who took one or more overseas trips. People who did not take an overseas trip are not counted in the base because the base calculation considers empty levels to be Null. Table 8: Tabulating variables from parallel levels The next table crosstabulates a variable from the vehicle level (vehicletype) with a person-level variable (gender). If you refer to the diagram that shows the levels structure of The Household Sample, you will see that the person and vehicle levels are parallel to each other (on different branches of the tree). This means that the data at the two levels is not directly related to each other. It would therefore make no sense to generate results at either the person or vehicle level and so this is not allowed. However, you can generate resultsatahigherlevelthatisanancestorof both of them. In this example, the only level that is an ancestor of both the person and vehicle levels is the top level. ach cell therefore shows the number of households that have the various types of vehicles and that contain people of the given gender. To create this table, expand the Vehicle loop and add the vehicletype variable to the side of the table, then expand the Person loop and add the gender variable to the top.

287 273 Tabulating Hierarchical Data Figure Tabulating variables from different parallel levels Table 9: Tabulating variables from higher levels atalowerlevel You can also tabulate higher level variables at a lower level, provided that the variables are on thesamebranchofthestructureandarenotonparallel branches. The next table crosstabulates two top-level variables (housetype and region) as for table 1, but this time is populated at the person level. To create this table, use the same table structure as in table 1, but this time change the level to person. Figure Tabulating variables from higher levels at a lower level The counts in the cells refer to people rather than households. Notice that the cell in the top left corner of the table shows that there are 25 people in the sample. Notice that we set the generation level for tables 3, 5, 7, and 9. For all of the other tables, we used the default level: Table 1 has two top-level variables only, so the default level is the top level. Table 2 has two person-level variables only, so the default level is the person level. Table 4 has two trip-level variables only, so the default level is the trip level. Table 6 has one person-level variable and one trip-level variable. The trip level is a child of the person level, so the default level is the trip level.

288 274 Chapter 11 Note: The Level header/footer field shows the generation level for the table. By default, this is shown in the right header position. You can change this if required. For more information, see the topic Changing Headers and Footers in Chapter 15 on p xample Showing Summary Statistics of a Numeric Variable in Cell Contents Table generated at trip level In the next table, the cell contents show not only the counts, but also the sum and mean summary statistics of the DaysAway numeric variable. This is a trip-level variable that stores the length of the trip in days. The sum values show the total number of days away and because the results are generated at the trip level, the mean values show the mean number of days per trip. Figure Summary statistics of a numeric variable in the cell contents - generated at Trip level To create this table: xpand the Trip grid within the Person loop, and add the purpose variable to the side. Add the gender variable from the Person loop to the top. Open the Table Properties tab (F4) and in the Cell Contents tab, add Sum to the list of items to include in cells. Select Sum, and in the Based on field at the bottom of the tab, select person[..].trip[..].daysaway.

289 275 Tabulating Hierarchical Data Add Mean to the list of items to include in cells, and base it on person[..].trip[..].daysaway as in the previous step. Choose OK to apply the settings to the table, and generate the results. Let s look at the three figures in the top left cell of the table. The first figure is 24, which corresponds with the base in the fourth table shown above, which tabulates two trip-level variables at the trip level. This figure shows the total number of overseas trips that were taken. The next figure is 320, which is the total number of days for all the trips. The final figure is the mean, which shows the average number of days per trip. Table generated at person level If we now generate results at the person level, the sum values will stay the same but the mean values will show the average number of days per person instead of per trip. Here is the table with results generated at the person level. Figure Summary statistics of a numeric variable in the cell contents - generated at Person level To create this table, use the same table specification and cell contents as for the previous table, but change the level to person. Let s look at the three figures in the top left cell of this new table. The first figure is 12, which corresponds with the base in Table 7 in xamples Showing Results Generated at Different Levels, which tabulates the same variables at the person level. This figure shows the total number of people who have taken at least one overseas trip. The next figure is 320, which is the total number of days for all the trips. This figure is the same as when we generated the results at the trip level.

290 276 Chapter 11 However, the mean value is now 27, because it now shows the average number of days away per person instead of per trip. Understanding Grid Tables The Creating tables using grid variables topic in the Using Variables section provides an introduction to grid tables and gives step-by-step instructions for creating a grid table. This topic provides more detailed information about grid tables and how they work. You can create grid tables from any grid or loop that is defined in the metadata as expanded, regardless of whether the data was actually collected using a grid question in the questionnaire. To see how grid tables work, look at the rating grid question in the Household sample. This grid question is nested inside the vehicle loop and so its full name is vehicle[..].rating (which we can optionally shorten to vehicle.rating). This grid question asks respondents to select a rating category for some of the vehicle s features. Grid questions can be considered as categorical loops, which are loops in which a category list defines the iterations and the iterations are presented simultaneously in a grid-like format. The category list that defines the iterations is sometimes referred to as the controlling category list. One or more variables inside the loop define the question(s) to ask for each iteration. The rating grid contains one variable (called Column), which has a category list that defines the rating categories. The following diagram shows how the grid in the Variables pane relates to the grid question when it is presented in a paper questionnaire. Figure Grid question in Variables pane and in questionnaire

291 277 Tabulating Hierarchical Data In this example, each iteration of the grid forms a row of the grid question as it is presented in the paper questionnaire. The columns of the grid question are formed from the categories of the Column variable inside the grid. This variable s full name is vehicle[..].rating[..].column. To create a grid table for the rating grid, select the grid in the Variables pane and choose the Add Grid/Loop button on the Design tab. The variable name on the top of the table consists of the full name of the rating grid and the name on the side consists of the full name of the variable (Column) inside the grid. Figure Grid table specification showing full names of variables Here is the table: Figure TableofRatinggrid

292 278 Chapter 11 When you create a grid table using the Add Grid/Loop button, IBM SPSS Data Collection Survey Reporter orients the grid table according to the default orientation defined for the grid or loop in the metadata. In this grid table, the iterations are displayed as columns because that is how the loop s default orientation is definedinthemetadata. Changing the orientation of the table If you do not want to use the default orientation, you can create the grid table using the opposite orientation, by choosing the Transpose button on the tool bar: Figure Transpose button Here is the table, in which the iterations now form the rows: Figure Table of rating grid with iterations as rows The table specification has been added to the footers for these tables. This has the following form: Side axis specification * Top axis specification Notice that in the specifications for the two tables the top and side specifications are reversed. Grids and loops that contain more than one variable The vehicle.rating grid contains only one variable the Column variable. However, some loops contain more than one variable. When you use the Add Grid/Loop method with a grid or loop that contains more than one variable, all of the variables that are contained in the loop are concatenated together in the grid table. Any non-categorical variables that are inside the loop and do not have an axis specification defined are ignored. For example, in the Household sample, the person loop is defined as expanded (which means that you can use it to create a grid table) and contains more than one variable, so you can use it in this way.

293 279 Tabulating Hierarchical Data TheBaseinGridTables If you look at the grid tables shown in the Understanding Grid Tables topic, you will see that unlike a standard table, there is either a base row or column, but not both. Specifically, the base is shown when the rows or columns are created from the variable inside the grid and not when they are formed from the iterations. The base is calculated in both the rows and columns, but it is not displayed for the iterations, because it can be confusing. To illustrate how the base for the iterations works, we will look at some tables that show this base. These tables were created using IBM SPSS Data Collection Survey Reporter Professional because in IBM SPSS Data Collection Survey Reporter, you cannot show the base for the iterations. Here is a table for which the results have been generated at the default level (the level above the grid, in this case, vehicle), which shows the base on both sides of the table: Figure Table with results generated at default (vehicle) level When the results for this grid table are generated at the vehicle level, each cell shows the number of vehicles for which the given category was chosen in that iteration. In other words, in this table each case is a vehicle. The base therefore shows the total number of vehicles.

294 280 Chapter 11 Now let s look at the same table when results are generated at the grid level, which in this example is the rating level (the header displays the level as Features because this is the description text for the rating grid): Figure Table with results generated at grid (rating) level When the results are generated at the level of the grid, each cell shows the number of responses for the given category in that iteration. This means that in this table each response to the rating question in each iteration is a case. The base therefore shows the total number of responses in all of the iterations. However, because each iteration was asked once for each vehicle, the number of cases in all the other cells is the same asinthetablewhereresultsweregenerated at the vehicle level. Setting up bases for grid iterations The following example demonstrates how to setup bases for grid iterations to include all respondents. The base expressions includes a higher-level question that forces the base to include null values: double[0..100] precision(5) scale(1) axis("{base1 'Base' base() [IsHidden=True], b 'Base' base('^.respondent_number is not null') [IsHidden By default, null iterations are omitted because they can hinder performance. The valuatemptyiterations custom property must be applied to the grid in the metadata in order to override the default behavior. For example: Grid_A "Attitudinal equity score" [ valuatemptyiterations =true ] loop When valuatemptyiterations custom property is set to true, all iterations, including empty iterations that do not exist in the CDSC, are returned.

295 281 Tabulating Hierarchical Data Refer to the Custom Properties in Use in IBM SPSS Data Collection Products topic in the IBM SPSS Data Collection Developer Library for more information regarding custom properties. Tabulating Grid and Loop Slices Sometimes you may want to tabulate the results of one iteration of a grid or loop against another variable. An iteration of a grid or loop is sometimes called a slice. Although you cannot create grid tables when you are using the flat view of the data, you can tabulate grid and loop slices. The examples in this topic use the Household sample, which uses the hierarchical view and cannot be represented in a flat form. However, the main principles of working with grid and loop slices are the same in both the hierarchical and the flat view and this topic explains the differences. To tabulate a slice of a grid variable In the Household sample data set, suppose you want to tabulate the rating that respondents gave to the vehicle s comfort by another variable (such as the vehicle type). Here is the grid question with the comfort slice highlighted: Figure Rating grid question To create a crosstabulation of this grid slice by the vehicletype variable: Create a new table. In the Variables pane, expand the vehicle loop. Drag the vehicletype variable that is nested within the loop and drop it on the Add button on thesideofthetable: In the Variables pane, expand the rating grid that is inside the vehicle loop, and then expand the Column variable that is inside the rating grid. Select the Comfort slice and choose Add on the top of the table. Choose the Generate table button: Figure Generate table button

296 282 Chapter 11 Here is the table: Figure Table showing type of vehicle by comfort rating To tabulate a slice of a numeric loop You can use a slice of a numeric loop in a similar way, provided the loop is defined as expanded. In a numeric loop, the iteration ID is a numeric value, rather than a category name. For example, suppose you want to tabulate the gender of the first person in each household by the region. You woulddothisasfollows: Create a new table. In the Variables pane, expand the person loop, and then expand the gender variable that is inside the person loop. Select the first slice (1) andchooseadd on the side of the table. In the Variables pane, select the region variable and choose Add on the top of the table. Choose the Generate table button: Figure Generate table button

297 283 Tabulating Hierarchical Data Here is the table: Figure Table showing gender by region of main residence Notice that in this table, the label in the side axis is 1: Gender. When you use a slice of a grid or loop in a table, the full label is used instead of the normal label. This makes it clear which slice is being used, because, by default, the full label is the label prefixed by the iteration name. When working in the hierarchical view the default generation level for a table is generally the lowest common ancestor level of all the filters and variables that are included in the table (including variables used in cell contents). However, when a table contains a grid slice at a lower level than any other variable included in the table, the default level will be the level above the grid slice. This is because, when tabulating a grid slice, it is more common to want to show the number of cases at the next level up rather than the number of responses at the grid level. However, you can choose to generate the table at the level of the grid slice if necessary. Filtering Hierarchical Data This topic provides a number of examples to illustrate how filters and expressions work when you are using the hierarchical view of the data. The examples are based on the Household XML sample. For more information, see the topic The Household Sample on p The first table is an unfiltered table at the Person level: Axis Side Top Variables The top-level Region variable. The Person-level Gender variable nested inside the top-level NumRooms variable.

298 284 Chapter 11 Here is the table: Figure Unfiltered table showing region by number of rooms Now let s add a filter to the table to select females only. We do this by creating a person-level filter, because the gender variable is at the Person level. Figure Table showing region by number of rooms, filtered to show females only To specify the level of a filter, click the Level button in the Filter tab. Now suppose you also want to create a global filter based on the top-level numrooms variable to select households that have less than eight rooms. Because this variable is at the top level, we will create the global filter at the top level. Note that the level of a new filter automatically defaults to the top level, so you would not need to set the level explicitly. Here is the table after applying both filters: Figure Table showing region by number of rooms, with local and global filters

299 285 Tabulating Hierarchical Data When you specify multiple separate filters like this, IBM SPSS Data Collection Survey Reporter automatically down-levs the expressions to the level of the lowest table filter and combines the resulting expressions using the And operator. Adding advanced filters using the Filter Syntax pane When you create a filter, all of the variables in the filter expression must be at the level of the filter. However, you can include variables from a higher parent level by down-leving them. For example, you can create a single Person-level filter that is identical to the combined separate Person-level and Top-level filters described above by adding the NumRooms variable to the Person-level filter. When you use the Filter tab, Survey Reporter automatically down-levs the NumRooms variable to the Person level if the level of the filter is defined as the Person level. If you display the Filter Syntaxpane, you will see the filter expression is as follows: gender.containsany({female}) AND ^.numrooms<8 The numrooms variable is preceded by the down-lev operator (^.). This filter selects women and girls who live in households that have less than eight rooms, just as the combination of the two separate filters does. You can include variables from a lower child level in the Filter Syntax pane by using the syntax for up-leving them. For example, if we wanted to create our filter at the top level, we could up-lev the Gender variable. However, it is not possible to create the previous filter at the top level. We can either select households that contain at least one female and less than eight rooms: SUM(person.(gender.ContainsAny({Female}))) AND numrooms<8 which gives this table: Figure Table showing region by number of rooms, with filters Or we can select households that contain no males and less than eight rooms: Sum(Person.(Gender = {Male})) = 0 And NumRooms < 8

300 286 Chapter 11 which gives this table: Figure Table showing region by number of rooms, with filters However, it is not possible to create a top-level filter to select females only, because that information is not available when you up-lev the data to the household level. The reason for this is that all of the Person-level data for each household is collapsed together. The syntax for up-leving data is the up-lev operator (.( ) in combination with one of the aggregate functions supported by the Data Model (Sum in this example). When creating multiple filters at different levels for individual tables, the filter levels must have a direct parent-child relationship with each other and not be parallel to each other (on different branches of the tree). For example, using the Household sample data, you cannot create separate filters at the Person and the Vehicle levels for the same table, because these levels are parallel to each other. However, you can create separate filters for the same table at the Person level and Trip levels, because the Trip level is a direct descendent of the Person level. If you need to filter a table on variables from parallel levels, you must create the filter at the first common ancestor level and up-lev the variables from one of the levels to the first common ancestor level and then down-lev the data to the level of the filter. If you are working in the Filter tab, you simply need to set the level of the filter and then select the variables, and Survey Reporter takes care of the up-leving and down-leving for you. However,whenyouareworkingintheFilterSyntaxtab,youneedtospecifytheexpression correctly. Here is an expression for a Person-level filter that uses the vehicletype variable from the parallel Vehicle-level: Gender = {Male} And ^.Sum(Vehicle.(VehicleType = {Motorbike})) > 0 The Household Sample The Household sample provides an example of a complex hierarchical data set. Unlike the Museum and Short Drinks samples, which are based on real surveys, the Household sample has been created artificially to demonstrate hierarchical data. The Household sample is a small data set that includes a very small number of cases at each level. This is to illustrate what happens when you generate your tables at different levels.

301 287 Tabulating Hierarchical Data Two versions of the Household sample are available a IBM SPSS Quanvert database and an XML data set. The two versions are slightly different and in this documentation we will be using the XML version. By default, the Household XML survey data is installed with the IBM SPSS Data Collection Developer Library in [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\DDL\Data\XML. The Household sample represents the data collected using the following fictitious survey: Household questions. Respondents are first asked a number of questions about their household as a whole, such as the address, age of the building, and number of rooms. Person questions. Respondents are then asked a number of questions about each person in the household, such as the person s name, age, gender, and occupation, and a grid question that asks the number of days he or she watches various TV channels. Overseas trip questions. Respondents are also asked a number of questions about each overseas trip that each person in their household has taken in the previous year (if any), such as the purpose of the trip, number of days he or she was away from home, and countries that were visited. Vehicle questions. Finally, respondents are asked a number of questions about each vehicle that belongs to their household, such as the vehicle s type, color, and annual mileage, and a grid question that asks the respondent to rate the vehicle s features.

302 288 Chapter 11 Figure Flowchart of questionnaire logic

303 289 Tabulating Hierarchical Data Loops called person, trip, and vehicle are used to ask the person, overseas trip, and vehicle questions, respectively. The person loop is an expanded loop that was iterated once (and therefore the questions were asked once) for each person in the household up to a maximum of six people. The other loops are unbounded loops that were iterated (and therefore the questions were asked) as many times as necessary. For example, in a household with three vehicles, the vehicle loop will be iterated three times, whereas in a single-vehicle household it will be iterated once. In a household that has no cars, bikes, or other vehicles, the vehicle questions will not be asked at all and the vehicle loop will have no iterations. Click below to see a diagram that lists the variables. Figure Diagram of variables The structure of the levels corresponds to the structure of the loops. This means that because the trip loop is nested within the person loop, the trip level is a child of the person level. The two grids, tvdays and rating, are also represented in the case data as levels, each nested within its parent level. Click below to see a diagram that shows the relationship of the levels.

304 290 Chapter 11 Figure Structure of levels

305 Chapter 12 Access Settings for Files on the Server Whenworkingwithafile on the server, a user s access settings determine what actions that user can perform. These access settings apply regardless of whether the user is working with the file from the Web interface or opening an existing file from the desktop interface using the Open from IBM SPSS Data Collection Interviewer Server Administration feature. The information in this section is intended mainly for IBM SPSS Data Collection Survey Reporter administrators. However, it may also be useful to users wondering why certain Survey Reporter features are unavailable. Users should contact their Survey Reporter administrator for information regarding their own specific access settings. Access Levels in IBM SPSS Data Collection Survey Reporter There are three standard access levels that apply to working with files on the server: Minimum Access: Users with this access level can open existing files on the server, generate tables, and export results. Medium Access: Users with this access level can create new files on the server, save existing files, and perform a variety of editing functions unavailable to users with Minimum Access. Full Access: Users with this access level have unrestricted access to all the features of IBM SPSS Data Collection Survey Reporter, including the ability to edit global settings. Note: The default installation of Survey Reporter provides Full Access. For other users opening files from the server, access level is set through the User Administration activity in IBM SPSS Data Collection Interviewer Server Administration. For users with several Interviewer Server Administration roles that each have different access levels, the least restrictive access level applies. Sample Roles Three sample roles corresponding to the above access levels are created at installation. ach role is set up with the appropriate Survey Reporter features. You can attach users to these roles if required, or base your own roles on them. The table below shows the features assigned to each role. Survey Reporter Feature TabulationMinimumAccess TabulationMediumAccessTabulationFullAccess Creating a new file No Yes Yes Opening an existing file Yes Yes Yes xporting tables Yes Yes Yes xporting data No Yes Yes Generating tables Yes Yes Yes Creating new tables No Yes Yes Creating and editing variables No Yes Yes Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

306 292 Chapter 12 Survey Reporter Feature Creating and editing filters Viewing a IBM SPSS Data Collection global filter TabulationMinimumAccess TabulationMediumAccessTabulationFullAccess No Yes Yes No No Yes View Script for All Tables... No No Yes option View Detailed Statistical No No Yes Output option MinimumAccess level Yes No No MediumAccess level No Yes No FullAccess level No No Yes The Access Definition File The MinimumAccess, MediumAccess, and FullAccess Interviewer Server Administration Tabulation features define the access restrictions that are applied to menu options, dialogs, windows, or other settings in Survey Reporter. The restrictions for each feature are specified in the Survey Reporter access definition file, access.xml. By default, this file is installed in the C:\InetPub\wwwroot\SPSSMR\TabulationWebService\AccessControl folder. The example below shows the default access.xml file installed with Survey Reporter. The file specifies the three default access levels and their restrictions. The two restricted access levels contain a list of settings, each of which disables access to a specific part of the Survey Reporter user interface. The FullAccess level has no restrictions and therefore no settings. Note that the option to view unweighted data is not included in any of the access levels. This option is controlled through a separate option in the User Administration activity. For more information, see the topic Viewing Unweighted Data on p <?xml version="1.0" encoding="utf-8"?> <Access> <Feature id="minimumaccess"> <Setting id="ditvariablesdisabled"/> <Setting id="definetabdisabled"/> <Setting id="advanceddefinedisabled"/> <Setting id="documentpropertiesdisabled"/> <Setting id="globalfilteringdisabled"/> <Setting id="weightingdisabled"/> <Setting id="toolsmenudisabled"/> <Setting id="tablesmenudisabled"/> <Setting id="optionsdisabled"/> <Setting id="tablecreationdisabled"/> <Setting id="tabledeletiondisabled"/> <Setting id="filesavedisabled"/> <Setting id="filenewdocumentdisabled"/> <Setting id="toolsheaderfooterdisabled"/> <Setting id="filesaveasdisabled"/> <Setting id="preferencestabdisabled"/> <Setting id="ditaxisdisabled"/>

307 293 Access Settings for Files on the Server <Setting id="ditannotationsdisabled"/> </Feature> <Feature id="mediumaccess"> <Setting id="toolsmenudisabled"/> <Setting id="ditvariablesdisabled"/> <Setting id="advanceddefinedisabled"/> <Setting id="preferencestabdisabled"/> </Feature> <Feature id="fullaccess"></feature> </Access> </?xml> Configuring Access Levels for IBM SPSS Data Collection Survey Reporter If required, you can change the settings defined for a particular feature by editing the access definition file to add or remove settings. Caution: The access restrictions specified for each feature in the default access definition file have been tested together to ensure that they provide the appropriate access levels for users. If you add or remove settings from any of the features, you must test the user interface thoroughly to ensure that the combination of restrictions you have specified results in a usable interface. Viewing Unweighted Data By default, users can view unweighted data through various options on the Web and desktop interfaces of IBM SPSS Data Collection Survey Reporter. To disable this option, administrators can set the Can ONLY view weighted data option in the User Administration activity in IBM SPSS Data Collection Interviewer Server Administration. Users with this restriction cannot open files that do not contain any weighting variables. For the files that do contain weighting variables, any Survey Reporter options that would allow the user to view unweighted data are disabled. Note that the option to restrict a user from viewing unweighted data is not included in any of the sample roles that are installed with Survey Reporter, and cannot be added to the access definition file. The setting must be separately applied using the User Administration activity. For more information see the Interviewer Server Administration User s Guide.

308 Versions Chapter 13 As a survey progresses, changes are sometimes made to the questionnaire. For example, questions and categories may be added and deleted. Typically a new version is created in the metadata each time a change is made to the questionnaire and each version corresponds to a variation of the questionnaire used for some of the interviews. When you load a data set that contains more than one version, all of the versions are combined to form a superset (sometimes called a superversion). This means that all of the variables and categories from all of the versions are available. When there is a conflict between, for example, a text in one or more of the versions, the more recent versions generally take precedence over the older versions. However the order of questions and categories is always taken from the most recent version. Case data collected using IBM SPSS Data Collection Interviewer Server has the name of the version used to collect it stored in a system variable called DataCollection.MetadataVersionNumber. You can use this to filter case data based on the version used to collect it. Typically you would create the filter as a global filter, which means that it will be applied to all tables automatically. Note: In data collected using tools other than Interviewer Server, the DataCollection.MetadataVersionNumber system variable may not store the name of the version, depending on how the data was set up. xample Using Multiple Versions This topic is designed to help you understand working with a data set that has multiple versions. The examples in this topic use the Short Drinks sample data. The following table provides details of the important differences in each of the five versions in the Short Drinks sample.mdd file: Version Name Description 1 This version was created when the IBM SPSS Data Collection Interviewer Server project was activated in test mode and was used for collecting test data. Five cases were collected using this version. 2 This version was created when the Interviewer Server project was first activated in live mode. 45 cases were collected using this version. There were no significant changes in this version. 3 In this version a new category (Fulltime parent) was added to the sclass question. 24 cases were collected using this version. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

309 295 Versions Version Name Description 4 In this version the 7 or more people category was deleted from the hhsize question and the text on the 6 people category was changed to 6 or more people. 20 cases were collected using this version. 5 In this version the text of the Fruit drinks category in the numdrksz question was changed to Fruit and vegetable drinks and the sclass categorical question was deleted and replaced with an open-ended question called occup. 27 cases were collected using this version. Here is an unfiltered table of hhsize by gender. Figure 13-1 Table showing Household size by Gender Notice that all of the categories are present, including the 7ormorepeoplecategory that was deleted in version 4. This is because IBM SPSS Data Collection Survey Reporter always uses a combination of all of the versions in the metadata. (This is sometimes called a superversion). The text on the 6ormorecategory reflects the text in the latest version and the order of the categories reflects the order of the latest version, except that the category that was deleted in version 4 has been added at the end. You can reorder the categories and change their texts using the dit Variable dialog box. For more information, see the topic dit Variable dialog box in Chapter 7 on p. 156.

310 Creating Profile Tables Chapter 14 In addition to creating tables to analyze survey data, you can also create tables that simply display the responses to one or more questions for all respondents or for selected respondents. These tables are called profile tables. Profile tables are useful for getting a quick overview of the responses in a survey. For example, you may want to get a rough idea of the distances travelled by respondents who have visited the museum several times in the past year. For an example of how to create a profile table, see Creating Profiles of Respondent Data in the Getting Started section. Creating a Profile Table You create profile tables by selecting variables on the Variables pane and adding them to the Design pane, then generating the results as you do for aggregated tables. To create a profile table From the menu, choose: Tables > New > Profile or press Ctrl+R. In the Design pane, enter a description for the profile table. In the Variables pane, highlight a variable, or use Shift+click or Ctrl+click to select multiple variables, and drag to the Design pane to add the variable(s) to the profile: Figure 14-1 Adding a variable to a profile table From the menu, choose: Tables > Generate Results or press F5, or choose the Generate Results button: Figure 14-2 Generate table button Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

311 297 Creating Profile Tables Saving Profile Data You save profiles in a table document (.mtd) file, together with aggregated tables. By default, both the structure of the table and the results are saved. Profile tables can take up a lot of space, but are relatively quick to generate. You may therefore find it quicker to save the structure of profile tables without the data, and just regenerate the profile tables again as you need them. To save the structure of profile tables without the data From the menu, choose File > Properties In the File Properties dialog box, choose the Advanced tab. Deselect the Keep profile data when saving check box. Note that only the profile data is discarded; the structure and properties of the profile tables are saved as usual when you save your tables. To save tables From the menu, choose File > Save In the Save dialog box, browse to a folder where you want to save your results. In the File Name field, enter a name for the file and choose Save. This saves both aggregated tables and profile tables.

312 Presenting Your Results Chapter 15 This section contains information on how to change the way in which your results are displayed, including sorting results and adding headers and footers. Sorting Tables Sometimesitisusefultosortyourtables,sothat you can see at a glance which is the most important or popular response. Sorting tables is sometimes called ranking. Tounderstand how it works, consider an unsorted table from the Museums sample data set, displaying What Respondents Remember by Holds Biology Qualification (some of the rows have been hidden to produce a shorter table for convenience; this does not affect the discussion in this topic): Figure 15-1 Remember by Biology - unsorted The rows and columns in the unsorted table are displayed in the order in which they are stored in the source data file. Suppose you want to sort the table so that the rows that contain more respondents appear before those containing fewer respondents. When you sort rows, you need to select the column on which you want to sort. For example, you could sort the rows by their values in the base column, by selecting biology{base} in the Sort rows based on list box of the Sort tab in the Table Properties dialog box. For more information, see the topic Sorting a Table on p Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

313 299 Presenting Your Results Here is the resulting table: Figure 15-2 Remember by Biology - sorted on Base column If you compare this table with the unsorted table, you will notice that the rows have been reordered, making it easy to see which categories were most popular. Although you generally want to sort the rows on the base column, you are not restricted to doing this. For example, you can sort the rows on the values in the Yes column, by selecting biology{yes} in the Sort rows based on list box. Here is the table: Figure 15-3 Remember by Biology - sorted on Yes column Notice that the order of the rows has changed to reflect the values in the Yes column. You can sort the columns, just like you can sort the rows. When you sort columns, you need to specify the row on which you want to sort. For example, you can sort columns by their values in the base row by selecting remember{base} in the Sort columns based on list box.

314 300 Chapter 15 Here is the table: Figure 15-4 Remember by Biology - sorted on Base row Notice that now the order of the Yes and No columns has been reversed, making it easy to see that more respondents chose the No category. And of course, you can sort both rows and columns in the same table, by selecting remember{base} in the Sort columns based on list box and biology{base} in the Sort rows based on list box. Here is the table: Figure 15-5 Remember by Biology - sorted on base row and column You can also sort tables on the first or last row or column in the table, without referring to a specific row or column name. This can be useful if you are running tracking studies to monitor change over time, as you can reuse the same table with each wave of data without having to re-select the row or column to sort on. For example, if you have a table containing monthly data, you can select Last column to sort the table by the latest month, rather than selecting the name of the month each time you update the data.

315 301 Presenting Your Results By default, sorting is carried out in descending order. However, you can sort tables in ascending order by choosing the ascending order option button. For example, here is the same table as the previous one, but sorted in ascending order: Figure 15-6 Remember by Biology - sorted on base row and column in ascending order You have probably noticed that all of the tables shown in this topic have only one item of cell contents and you may be wondering what happens when the table contains additional cell contents. The answer is that if the table contains more than one item of cell contents, the sort is always basedonthefirst item of cell contents. When creating sorted tables that contain more than one item of cell contents, you therefore need to give some consideration to the order in which you specify the items. Notes and General Limitations If there is more than one item of cell contents, the firstitemisalwaysusedforthesort. Sorting rows that contain cumulative column percentages or columns that contain cumulative row percentages is not recommended, as the reordered percentage values do not give meaningful results. The side or top of the table is not sorted if it contains a combination of nesting and concatenation (multiple added variables). You cannot use an element that is inside a net to sort the other axis of the table. You cannot sort an axis that contains net elements in an outer nest level. Any sorting that would apply is ignored. There are a number of special rules that apply when sorting axes that contain special elements. For more information, see the topic Sorting Special Items on p Sorting a Table You can sort tables on rows, columns or specific items, in ascending or descending order. For more information, see the topic Sorting Tables on p. 298.

316 302 Chapter 15 To sort a table In the Tables pane, select the table that you want to sort. From the menu, choose: Tables > Properties Choose the Sort tab. In the Sort rows based on or Sort columns based on drop-down list, choose the column or row that you want to sort on. Alternatively, choose one of the First/last row/column options. These options are useful if you add new categories to your surveys over time and you want to reuse the tables. For example, if you have a table containing monthly data, you can select Last column to sort the table by the latest month, rather than selecting the name of the month each time you update the data. If required, you can sort on both rows and columns. Note: To sort columns, you select the row on which to sort, and vice versa. Choose ascending order or descending order as required. Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. Generate the table to see the results of your changes: Figure 15-7 Generate table button Note: You cannot apply sort options to multiple tables, as the options available depend on the rows and columns in individual tables. Sorting Tables With Multiple Added or Nested Variables Tables with Multiple Added Variables When you sort a table that has multiple variables in the dimension in which you are sorting, where the variables have been added using the Add button, the elements within each variable are sorted separately. For example, the following table uses the Museums sample data set, with Age and Gender added on the side of the table, and Biology and Before on the top of the table. The rows are sorted by their values in the Before column.todothis,youselectbefore{base} from the Sort rows based on list box in the Sort tab of the Table Properties dialog box. For more information, see the topic Sorting a Table on p. 301.

317 303 Presenting Your Results Here is the table, with the sort column highlighted: Figure 15-8 Table with multiple added variables sorted on base Before column Notice that the rows that relate to the Age variable have been sorted separately from the rows that relate to the Gender variable. Table with Multiple Nested Variables If there is nesting in the dimension of the table in which the sort row or column is located, the sorting list boxes display the combined sort options. In the following nested table, the rows are sorted on the Base column of the Before variable that is nested within the Yes category of the Biology variable. To do this, you select the biology{yes} > before{base} option from the Sort rows based on list box. Here is the table, with the sort column highlighted: Figure 15-9 Nested table sorted on base Before column Note that the sort order would be different if you sorted the rows on the Base column of the Before variable that is nested within the No category of the Biology variable. When you sort a table that contains nesting in the dimension in which you are sorting, the elements within the inner variables are sorted. However, the elements of the outermost variable are not sorted. For example, the following table has ducation nested within Interview on the

318 304 Chapter 15 side of the table, by Gender on the top of the table. The rows of the table are sorted by the values in the base Gender column. To do this, you select the Gender{Base} option from the Sort rows based on list box. Here is the table, with the sort column highlighted: Figure Nested table sorted on base Gender column; outermost variable is unsorted Combination of Added and Nested Variables You cannot sort an axis that contains a combination of nested and added (concatenated) variables. However, you can use that axis to sort the other axis of the table (provided that this does not also contain both nesting and concatenation).

319 305 Presenting Your Results Sorting Categories in Nets When you sort a table that contains nets, the categories within each net are kept together and sorted within the net. For example, the following unsorted table contains a number of nets: Figure Table with nets, unsorted You can sort the rows of the table by their values in the Base column by selecting Gender{Base} from the Sort rows based on list box on the Sort tab of the Table Properties dialog box. For more information, see the topic Sorting a Table on p. 301.

320 306 Chapter 15 Here is the sorted table: Figure Table with nets, sorted on base Gender column Notice that the categories within each net have been sorted, and that the net groups have been sorted, but that the categories within each net group have been kept together. Note that you cannot use a category inside a net to sort the other axis of the table. Nets in Nested Tables You cannot sort an axis that contains net categories in an outer nest level. Any sorting that would apply to the axis is ignored. Sorting Special Items There are a number of rules that apply when sorting tables that contain special items (anything other than a category). The default behavior depends on the item type. The following item types are sorted by default: Standard categories Nets Categories created by combining categorical variables Derived categories and user-defined categories. The following element types have a fixed position by default: Base Unweighted base Mean

321 307 Presenting Your Results Standard deviation Standard error Sample variance Subtotal Total Minimum Maximum When an item has a fixed position, it means that if the item is third in the unsorted table, it will be the third item in the sorted table and items that are sorted will move around it, when necessary. For this reason, it is usual to place unsorted items at the beginning or end of the category list. Text-only items are never sorted. Unlike nets, they are not tied to the items that follow. This means that text-only items are not generally suitable for use in sorted tables. For all item types apart from text-only items, you can change the default sort behavior using the Keep fixed when sorting property. For more information, see the topic dit Variable dialog box: Properties pane in Chapter 7 on p SortingGridTables You can sort the columns and rows of a grid table. For example, when you tabulate the Museum Rating grid table: Figure Rating grid you can sort the rows on one of the columns (which are formed from the categories of the variable inside the grid) and you can sort the columns on one of the rows (which are formed from the iterations).

322 308 Chapter 15 For example, in the following table, the rows are sorted on the Very Interested column, by selecting rating[..].column{very_interested_5} from the Sort rows based on list box on the Sort tab of the Table Properties dialog box. For more information, see the topic Sorting a Table on p Figure Grid table sorted on Very Interested column In the next table, the columns are sorted on the Dinosaurs row, by selecting rating{dinosaurs} from the Sort columns based on list box: Figure Grid table sorted on Dinosaurs row Note thatyoudonotnormallysortagridtableonthebaseroworcolumn.

323 309 Presenting Your Results Hiding Rows, Columns, and Cells You can hide rows, columns, or cells in your tables where all values are equal to, above, or below a value that you specify. This means that you can display tables without rows or columns containing insignificant values. For example, the following table contains both a row and a column that contain only zero values: Figure Tablecontainingrowandcolumnwithzerovalues By hiding rows and columns containing only zeros, you can simplify the table and display only the information of interest: Figure Table with zero value row and column hidden

324 310 Chapter 15 By default, all values in the first cell item in a row or column must be equal to zero for that row or column to be hidden, as in the above example. However, you can use the value in another row or column on the table to test the hide condition. For example, in the following table of interest by age, a column has been added to show the mean age: Figure Table of interest by age with added mean column If you are interested in the results for a particular age range, you can hide rows where the mean age column has a value of greater than 30: Figure Table of interest by age. Rows with a mean of greater than 30 are hidden Hiding a Row or Column You can hide rows or columns in your tables where the values are equal to, above, or below a value that you specify. To hide rows or columns In the Tables pane, select the table that you want to modify.

325 311 Presenting Your Results From the menu, choose: Tables > Properties Choose the Hide tab. Check the Hide rows or Hide columns box as appropriate. Alternatively, choose one of the First/last row/column options. These options are useful if you add new categories to your surveys over time and you want to reuse the tables. For example, if you have a table containing monthly data, you can select Last column to hide rows based on the value of the last month, rather than selecting the name of the month each time you update the data. If required, you can hide both rows and columns. Note: To hide columns, you select the row on which to hide,and vice versa. In the drop-down list, select the condition for hiding the row or column, and enter a value. For example, you might choose to hide rows where the values are less than 10. The default condition hides values less than or equal to zero. Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. Generate the table to see the results of your changes: Figure Generate table button To base the hide condition on a different row or column In the Hide tab, you can specify a different column or row to test the hide condition. Select the row or column from the based on drop-down list. For example, to hide all rows that have a value of less than 30 in the mean column of a variable called age,selectage{emean} from the drop-down list. Hiding Cells You can hide individual cells in your tables where the values are equal to, above, or below a value that you specify. For example, you might choose to hide cells containing values of less than 10. Note that when you hide cells, all the contents of a cell that meets the hide condition are removed, but the cell still remains on the table. To hide cells In the Tables pane, select the table that you want to modify. From the menu, choose: Tables > Properties Choose the Hide tab. Check the Hide cells box.

326 312 Chapter 15 In the drop-down list, select the condition for hiding the cell, and enter a value. For example, you might choose to hide cells containing values of less than 10. The default condition hides values less than or equal to zero. Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. Generate the table to see the results of your changes: Figure Generate table button Changing Headers and Footers You can add headers and footers to your tables to provide additional information, such as the name of the data file, details of filters, weighting, and a number of other pieces of information. You can display the information in up to eight different positions around the table. Figure Table showing headers and footers with HTML formatting, hyperlink, and image tags A number of predefined headers and footers are present by default. You can remove these or move them to other header and footer locations. You can also include your own text and you can add formatting, hypertext links, and images, using a number of standard HTML tags. When you export tables to other formats, the exact way in which the header and footer information is displayed depends on the type of export you use, and on the export options you select.

327 313 Presenting Your Results You can also set up global headers and footers. These are applied to all of the tables in the table document. If any other headers and footers are defined in the same position for any of the tables, they appear after the global headers and footers on those tables. Note that global headers and footers will be applied to any new tables that you create. Adding Headers and Footers You can change the headers and footers that are displayed on a table to show additional information about the table, such as the time it was created, the detailed table specification, or the name of the source data file. You can also define global headers and footers that apply to all the tables in the table document. To add headers and footers to a table In the Tables pane, select the table for which you want to change the headers and footers. From the menu, choose: Tables > Properties Choose the Header and Footer tab. Place the cursor in the header or footer position you want to change, for example, Center. Take care to position the cursor outside the field code markers {} of any existing fields. Choose the Insert Field button. In the Field Selection dialog box, select the field you want to add. As you select a field, details about the field appear at the bottom of the dialog box. For example, the DBLocation field contains the name and location of the case data. For more information, see the topic Field Selection on p If required, use the check boxes to the right of the field list to add optional settings for the selected field. For example, Add a text prefix adds predefined text such as Table: Filter:, Statistics: and so on, describing the selected field. Options vary depending on the field you select. Tip: Once you become familiar with the optional settings, you may want to choose the Field Codes button to display codes instead of descriptions, and enter the codes directly. For example, the field code for the Add a text prefix option is \p. Choose OK to close the Insert Field dialog box. If required, you can add more fields to the same header or footer position, or to other header or footer positions, in the same way. You can add your own text to a header or footer by typing it directly into the header or footer position text box, taking care to type outside the field code markers {} of any existing fields. For example, instead of using the standard prefix, you could add your own text prefix Survey data file infrontofthecasedatalocationfield, as follows: Survey data file: {DBLocation }

328 314 Chapter 15 You can add formatting such as italics, bold, or color to header and footer text, using a limited set of well-formed HTML tags. For more information, see the topic Adding Formatting to Headers and Footers on p You can also use the HTML tags to insert hypertext links or even images in your headers and footers. For more information, see the topic Adding Hypertext Links and Images to Headers and Footers on p Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. To define global headers and footers: From the menu, choose Tables > Global Header and Footer In the Global Header and Footer dialog box, choose a header or footer position that you want to define, for example, Footer Center. Add header and footer details in the same way as for table headers and footers. Choose OK to close the dialog box. Adding Formatting to Headers and Footers You can add formatting to headers and footers in your tables using a limited set of HTML tags. For example, you can change the font or make the text bold or italic. To add formatting to headers and footers In the Tables pane, select the table for which you want to change the headers and footers. From the menu, choose: Tables > Properties Choose the Header and Footer tab. In the header or footer position you want to change, place the cursor in front of the text that you want to format, and enter an opening HTML tag. This example highlights the word of in italics: {TableNumber \p} <i>of {TotalNumberOfTables \n} Place the cursor at the end of the text that you want to format, and enter the corresponding closing HTML tag: {TableNumber \p} <i>of</i> {TotalNumberOfTables \n} Note: To format a field code, place the formatting tags outside the field code markers {} as in this example, which highlights the table number and total number of tables in bold: <b>{tablenumber \p}</b> <i>of</i> <b>{totalnumberoftables \n}</b>

329 315 Presenting Your Results Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. For full details of the subset of HTML tags available for use in headers and footers, see HTML Formatting for Headers and Footers. Adding Hypertext Links and Images to Headers and Footers You can add hypertext links to headers and footers in your tables using the HTML <a> tag. You can also add images using the <img> tag. To add hypertext links to headers and footers In the Tables pane, select the table for which you want to change the headers and footers. From the menu, choose: Tables > Properties Choose the Header and Footer tab. Place the cursor in the header or footer position where you want to add the hypertext link, taking care to place the cursor outside any field code markers {}. nter the hyperlink tag. This example adds a link to the SPSS website: <a href=" Toaddanimage Place the cursor in the header or footer position where you want to add the image, taking care to place the cursor outside any field code markers {}. nter the image tag, including the path and filename of your image file, which must exist in the correct location. This example adds a logo that has been placed in a folder on the C:\ drive. <img src='c:\corporateimages\logo.png' alt='spss logo'/> Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. For full details of the subset of HTML tags available for use in headers and footers, see HTML Formatting for Headers and Footers. Adding Notes to Headers and Footers You can include notes that you have added to a table using the Table Notes pane, so that they appear as headers or footers in the Results pane. To add notes to a table In the Tables pane, select the table to which you want to add a note.

330 316 Chapter 15 If the Table Notes pane is not visible, choose View > Table Notes from the menu, or press Alt+6. nter the note in the Table Notes pane. Choose the Apply button to apply the note to the table. To include notes in a table header or footer In the Tables pane, select the table. From the menu, choose: Tables > Properties Choose the Header and Footer tab. Place the cursor in the header or footer position where you want to display the note, and type the following, including the curly brackets: {TableProperty:TableNotes} Choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. Regenerate the table to see the note. Moving or Deleting Headers and Footers You can move the text in a header or footer from one header or footer position and add it to another. You can also delete a header or footer from a table. See Header and Footer Positions for information on the recommended minimum information to include in headers and footers. To move headers and footers In the Tables pane, select the table for which you want to move the header or footer. From the menu, choose: Tables > Properties Choose the Header and Footer tab. In the header or footer position you want to change, for example, Left side, clickanddragto select all the text. Note: If you want to move part of a header or footer, you can select the specific textthat you want to move. If you move a field code you must select the entire code, including the field code markers {}. Press Ctrl+X to cut the text from the current location.

331 317 Presenting Your Results Position the cursor in the header or footer position where you want to place the text, taking care to place the cursor outside any existing field code markers {}. Press Ctrl+V to paste in the text. Repeat for any other headers or footers you want to move. To delete headers and footers Select the text you want to delete in the same way as for moving headers or footers. Press the Delete key. When you have finished making your changes, choose OK to close the Table Properties dialog box, save your changes, and apply them to the current table. Header and Footer Positions The following diagram shows the position of the headers and footers. Figure Header and footer positions You can set up the text to display in these positions for individual tables or as defaults to apply to new tables. Default Headers and Footers By default, a number of pieces of information are displayed in headers and footers. This information is automatically inserted using fields that are included in the header or footer position, asshowninthefollowingtable. Position Title Header Field Project description.

332 318 Chapter 15 Position Left Header Right Header Left Footer Field Table description and filters. Table number and description of the weighting variable, if any, and the level at which it was generated. Cell contents and information about the statistical tests, if any, and details of any hide rules that have been applied, as well as warning messages for statistical tests and explanations of symbols. See Field Selection for a full list of the fields you can add to your headers and footers. Recommended Information to include in Headers and Footers You should make sure that the following fields are always included in one of the header or footer positions. Without this information, the published tables can be misleading: Cell Contents Filters Weight Variable Statistics Level(ifyouareworkingwithhierarchicaldata) Populate Warnings Cell Item Symbols HTML Formatting for Headers and Footers You can use a limited number of HTML tags to insert hyperlinks or define formatting in texts to display in headers and footers (annotations). When possible, it is generally preferable to control the formatting of the headers and footers using the export style sheets rather than HTML tags embedded in the header and footer specifications. However, the HTML tags are useful when you want to emphasize individual words or phrases. Tag Attributes Description <b>...</b> Stong emphasis (bold). <i>...</i> mphasis (italics). <u>...</u> Underlined. <font>...</font> color size face Font. You can use the color attribute to specify a color, using either the hexadecimal value or the color name, the size attribute to specify a size from 1 (smallest) to 7 (largest), and the face attribute to specify a comma-separated list of font names in order of preference. <a>...</a> href Anchor. You can use the href attribute to insert the URL of a web page.

333 319 Presenting Your Results Tag Attributes Description <img/> src Image link. Specify the name and location of the alt graphic in the src attribute. You can also specify alternate text to appear when you move the mouse over thegraphicusingthealt attribute. (Note that this tag does not require a separate closing tag.) <br/> Inserts a line break. (Note that this tag does not require a separate closing tag.) The HTML tags used must be well-formed HTML, otherwise they may not be recognized as HTML and will appear as plain text. For example: You must close all tags. This is particularly easy to forget when using the <br> and <img> tags, which do not have separate closing tags. Specify the line break tag as <br/> and not <br>, or it may appear in the exports as <br>. Similarly, you need to close the <img> tag, for example: <img src='c:\corporateimages\logo.png' alt='spss logo'/> You must use the same case for opening and closing tags. You must enclose attributes in double or single quotation marks (for example, <font size='7'>). At the time of writing, information about well-formed HTML is available at Microsoft: Authoring Well-Formed HTML ( ( ). For examples of how to use these tags, see Adding Formatting to Headers and Footers and Adding Hypertext Links and Images to Headers and Footers. Global Headers and Footers Use the Global Header and Footer dialog box to define headers and footers that you want to appear on all your tables. If any other headers and footers are defined in the same position for any of the tables, they appear after the global headers and footers in those tables. To display this dialog box, choose: Tables > Global Header and Footer Fields on the Global Header and Footer dialog box The dialog box contains text boxes for each of the four header and four footer positions. Click in a text field to add, edit, or delete the relevant header or footer. All global headers and footers are empty by default. However, note that a number of headers and footers are supplied as defaults for all tables. To view or edit these default settings, use the Header and Footer tab of the Table Properties dialog box.

334 320 Chapter 15 Insert Field. Place the cursor in a header or footer text box and choose this button to open the Field Selection dialog box and select a field to add to the header or footer. For full details of the fields that you can add, see Field Selection. Displaying Results in Charts As well as displaying results in the form of a table, you can also display them as charts. You can also export results in chart format to HTML, and to Microsoft xcel, Word, and PowerPoint. You can use a variety of different charts, including custom chart formats. This section contains information about how you can display results in charts. Notes Displaying charts in IBM SPSS Data Collection Survey Reporter requires Microsoft Office Web Components (OWC) version 10 or later. However, this is not necessary if you want to display only tables. For information on installing Microsoft Office Web Components, see the IBM SPSS Data Collection Server Installation Guide. Charts are not available in the x64 64-bit version of IBM SPSS Data Collection. Displaying a Chart To display a chart in the Results tab From the menu, choose Tools > Options On the Display tab, select an option that includes charts, for example, Table and Chart in the Generate drop-down. Add variables from the Variables pane into the Design tab as you would when creating tables. Choose the Generate results button. To export to a chart From the menu, choose File > xport > Tables In the xport Tables dialog box, select an export option. You can export to charts using any of the export options except the Text File option. Choose the More button. If using the HTML or Microsoft Word export, choose an option that includes charts, for example, Table and Chart. If using the Microsoft xcel export, check the Display Charts box. In the Default chart type drop-down list (or the list beneath the Display Charts box if using xcel) select the type of chart you want to export to, for example, 3D Pie.

335 321 Presenting Your Results If you have set up a custom chart in xcel, to export your results in the custom chart format (available for Microsoft xcel, PowerPoint, or Word) type the name of the custom chart in the Defaultcharttypedrop-down list (or the list beneath the Display Charts box if using xcel). For more information, see the topic xporting Charts Using Microsoft xcel Custom Chart Types in Chapter 16 on p Adjust any other settings that you want to change, and choose the OK button. How Data is Displayed in a Chart Here is a chart created from a basic table of Age by Gender: Figure Chart of Age by Gender, with rows forming the chart series The default chart format is a clustered column chart based on column percentages. If a table does not contain column percentages, the chart is based on the counts, as shown in this example. For charts that do not contain either column percentages or counts, the charts are based on the first cell item. A chart will not be created for any tables that contain cell prefixes in the column percentage cells. Note that bases are omitted from the charts.

336 322 Chapter 15 By default, chart series are based on the table rows. You can base the chart series on table columns by deselecting the Chart table rows as series option in the relevant xport dialog box: Figure Chart of Age by Gender, with columns forming the chart series For concatenated and nested tables, a separate chart is created for each section of the table. For example, the following diagrams show the charts that are created for a concatenated and a nested table.

337 323 Presenting Your Results Here is the concatenated table: Figure Concatenated table and charts

338 324 Chapter 15 Here is the nested table: Figure Nested table and charts You can optionally create charts for statistical items in a variable (such as the mean, minimum value, standard deviation, etc.). If more than one such item is included in the table specification, or if the table includes a mixture of categorical and other items, a separate chart is created for each statistical item in the table. For example, a separate chart would be produced for each statistical item in the table shown in Adding summary statistics to a numeric variable. A chart is also produced when a numeric variable is banded. For example, a chart would be produced for the table shown in Creating bands.

339 325 Presenting Your Results Notes If a table contains no data, no chart is displayed. By default, charts are displayed for column percentages. For tables that do not contain column percentages, charts are displayed for counts. For tables that do not contain either column percentages or counts, charts are displayed for the firstcelliteminthetable. Charts are not saved in table documents. To see charts for a saved table document, you need to repopulate the tables. Chart Types By default, charts are clustered column charts based on column percentages. You can also choose from the chart types below. Click a link below to display an example chart and description. To hide the example, click the link again. Figure Clustered bar chart example Figure Stacked bar chart example

340 326 Chapter 15 Figure D clustered bar chart example Figure D Stacked bar chart example Figure Clustered column chart example

341 327 Presenting Your Results Figure Stacked column chart example Figure D clustered column chart example Figure D stacked column chart example

342 328 Chapter 15 Figure D column chart example Figure Line chart example Figure Stacked line chart example

343 329 Presenting Your Results Figure Line chart with markers example Figure % stacked line chart with markers example Figure Pie chart example

344 330 Chapter 15 Figure D pie chart example Figure Separated pie chart example Figure D separated pie chart example

345 331 Presenting Your Results You can select a chart type for an individual table using the Chart tab in the Table Properties dialog box. If you do not specify a chart type, the default chart type is used (this depends on the type of table, but in most cases is a Clustered Bar chart). When you export your results, you can select a chart type to use for the export. This becomes the default chart type for any tables for whichnocharttypeisspecified. It does not override chart types you have selected for individual tables using the Chart tab. When you export charts to Microsoft xcel, PowerPoint, or Word, you can optionally export the charts to a user-defined custom chart type that you have set up using xcel. For more information, see the topic xporting Charts Using Microsoft xcel Custom Chart Types in Chapter 16 on p Changing Table Properties You can change the properties of the tables that you create using the Table Properties dialog box. Changes that you make in this dialog box apply to the currently selected table(s) when you choose OK. Alternatively, you can change the default properties for all new tables, by choosing the Set as Default button. Note: The option to set defaults is not available in a number of the Table Properties tabs. This is because it is not possible to set defaults for some properties, for example sorting options, as this information is specific to the structure of an individual table. The properties that you can change depend on the type of table you create. Only the level, sort, and header and footer properties are applicable to profile tables. Table Properties: Cell Contents Use the options in the Cell Contents tab to change the items in cells of your tables. For example, instead of displaying counts in each cell of a table, you may want to display only column percentages, or you may want to add a mean or standard deviation. To display this tab, choose Tables > Properties from the menu and choose the Cell Contents tab.

346 332 Chapter 15 Figure Table Properties, Cell Contents tab Fields on the Cell Contents tab Available items. The following cell items are available. To add a cell item to the table, select it and choose the >> button to add it to the Included in cells list. Name Counts Column base Row base Purpose Shows the number of cases that satisfy the row and column conditions for each cell. If the table is weighted, the counts are the weighted counts. Shows the number of cases in the column base. This is shown in the base row of the table. This cell item is useful when the base row is hidden or when tables are so large that the row is not always visible. Shows the number of cases in the row base. This isshowninthebasecolumn of the table. This cell item is useful when the base column is hidden or when tables are so large that the column is not always visible.

347 333 Presenting Your Results Name Unweighted column base Unweighted row base Column percentages Cumulative column percentages Cumulative row percentages xpected values Indices Maximum Mean Median Minimum Mode Purpose Shows the unweighted base for the column. This is shown in the base row of the table. This cell item is useful when the unweighted base row is hidden or when tables are so large that the row is not always visible. Shows the unweighted base for the row. This is shown in the base column of the table. This cell item is useful when the unweighted base column is hidden or when tables are so large that the column is not always visible. xpresses the count or sum of a numeric variable as a percentage of the base for the column. xpressing figures as percentages can make it easier to interpret and compare the data in a table. xpresses the column percentages as cumulative percentages. xpresses the row percentages as cumulative percentages. Shows the count or sum of a numeric variable that would be expected in the cell if the row and column variables are statistically independent or unrelated to each other. Calculated for each cell by dividing the row percentage in the cell by the row percentage for the same column in the base row. Indices show how closely row percentages in a row reflect the row percentages in the base row. The nearer a row s indices are to 100%, the more closely that row mirrors the base row. This summary statistic of a numeric variable shows the largest value. This summary statistic of a numeric variable gives a measure of central tendency. It is the arithmetic average the sum divided by the number of cases who gave a response for the numeric variable. This summary statistic of a numeric variable shows the value above and below which half of the cases fall (the 50th percentile). If there is an even number of cases, the median is the average of the two middle cases when they are sorted in ascending or descending order. The median is a measure of central tendency not sensitive to outlying values (unlike the mean, which can be affected by one or more extremely high or low values). This summary statistic of a numeric variable shows the smallest value. This summary statistic of a numeric variable shows the most frequently occurring value. When several values share the greatest frequency of occurrence, each of them is a mode. IBM SPSS Data Collection Base Professional displays only one mode in each cell when there is more than one mode, Base Professional displays the first mode that it encounters in the data.

348 334 Chapter 15 Name Percentile Range Residuals Row percentages Sample variance Standard deviation Standard error Sum Total percentages Unweighted counts Purpose This summary statistic of a numeric variable shows the value that divides cases according to values below which certain percentages fall. For example, the 25th percentile is the value below which 25% of cases fall. This summary statistic of a numeric variable shows the difference between the largest and smallest values the maximum minus the minimum. Shows the difference between the count or sum of a numeric variable and the expected values. Large absolute values for the residuals indicate that the observed values are very different from the predicted values. xpresses the count or sum of a numeric variable as a percentage of the base for the row. This summary statistic of a numeric variable shows the sample variance, which is a measure of dispersion around the mean, equal to the sum of squared deviations from the mean divided by one less than the number of cases. The sample variance is measured in units that are the square of those of the variable itself. This summary statistic of a numeric variable shows a measure of dispersion around the mean. In a normal distribution, 68% of cases fall within one standard deviation of the mean and 95% of cases fall within two standard deviations. For example, if the mean age is 45 with a standard deviation of 10, then 95% of the cases would be between 25 and 65 in a normal distribution. This summary statistic of a numeric variable shows a measure of how much the value of the mean may vary from sample to sample taken from the same distribution. The standard error of the sample mean can be used to estimate a mean value for the population as a whole. In a normal distribution, 95% of the values of the mean should lie in the range of plus or minus two times the standard error from the mean. Additionally, the standard error can be used to roughly compare the observed mean to a hypothesized value of another mean (that is, you can conclude that the two values are different if there is no overlap in the values of the means plus or minus two times the standard error). This summary statistic of a numeric variable shows the sum or total of the values. xpresses the count or sum of a numeric variable as a percentage of the base for the table. In a weighted table, these are the unweighted counts. In an unweighted table, the counts and the unweighted counts are identical. Included in cells. This lists the cell items that you have selected to appear on the table. By default, counts and column percents are selected. To remove a cell item from the table, select it and choose the << button.

349 335 Presenting Your Results Move up/move down. Select an item in the Included in cells list and choose the Move up or Move down button to change the order in which cell items will be displayed in the table. Prefix. You can add text, for example, a currency symbol, before the cell contents. Highlight the cell item in the Included in cells list, and type the text in the Prefix textbox. Suffix. You can add text after the contents of a cell, for example, a currency abbreviation. Highlight the cell item in the Included in cells list, and type the text in the Suffix textbox. Decimal places. Available for all types of cell contents. Specify the number of decimal places with which you want the values to be shown. Based on. For summary statistics of a numeric variable, choose the numeric variable to use. For indices, residuals, expected values, and any of the percentage options, you can base the figures on counts or on the sums of a numeric variable if they have been specified for this table. The default is counts. If the table is weighted, these are the weighted counts. If you want to base the figures on the unweighted counts, you must remove the weighting from the table. For mean, sample variance, standard error, standard deviation, minimum, maximum, range, sum, median, mode, and percentile, you can select a specific variable, or select the dash (-). Selecting aspecific variable is suitable in cases where you want to show the mean for the same variable throughout the table. Selecting the dash tells IBM SPSS Data Collection Survey Reporter not to use a specific variable for the whole table, but instead to use the numeric variable specified in each category to calculate the mean for that category. This is useful if you want to create a summary statistic table where each category represents a different numeric variable. Note: You can set up summary statistic tables automatically using the Summary Statistic Table option on the Tables menu. For more information, see the topic Creating Summary Statistic or Summary MeanstablesinChapter4onp. 65. Percentile. Available for percentiles only, this enables you to specify the percentile required; for example, enter 25 for the 25th percentile. Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Display Use the options in the Display tab to change the way in which percentages are handled in your tables, to define the characters or symbols used to represent counts, percentages, and other values that are zero and are rounded to zero, and to define rounding options. To display this tab, choose Tables > Properties

350 336 Chapter 15 from the menu and choose the Display tab. Figure Table Properties, Display tab Fields on the Display tab Adjust rounding so that percentages add up to 100%. Percentages for tables created from single response variables do not always add up to 100% because of rounding. Check this box to manipulate single response percentages so that they add up to 100%. For more information, see the topic Rounding in IBM SPSS Data Collection Survey Reporter in Chapter 19 on p Show 100% in base row and column. Check this box if you want to show 100% in the cells of the base row for column percentages and in the cells of the base column for row percentages. Deselect if you want 100% to be omitted from these cells. Display percent signs. By default, this check box is selected. In tables containing only percentage values, you may not want to include percent signs. Deselect this check box to remove percent signs from the entire table. Values. Use the options in the lower part of the dialog box to define characters or symbols to represent counts, percentages, and other values that are zero or are rounded to zero. For each option, enter the character or characters of your choice in the Display as field.

351 337 Presenting Your Results Counts that are zero. The default is -. Counts that are rounded to zero. The default is *. Percentages that are zero. The default is -. Percentages that are rounded to zero. The default is *. Other values that are zero. The default is -. Other values that are rounded to zero. The default is *. To reduce confusion, avoid using for the zero symbols any of the 52 alphabetic characters in upper and lower case (A Z and a z) that are used for the column IDs in the statistical tests. Instead, consider using non-alphabetic characters or other text strings. Base counts below. Specify a minimum value for the base. No results are displayed in cells where the base is below this value. By default, the * symbol is displayed instead. If required, you can change this to another character or characters. If there are multiple bases because of nesting or because additional bases have been specified, the nearest base to the cell is used to determine whether to suppress the value in the cell. Rounding options. Provides options for defining rounding behavior. Round to even. When the decimal places are exactly 5 the number is rounded to the even integer. This means that of the two possible rounded values, the one that has an even number as the last significant digit is returned. For example, is rounded to 15.2 rather than Round up. When the decimal places are exactly 5 the number is always rounded up. For example, is rounded to 15.3 rather than Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Weight Use the options in the Weighting tab to add a weight to your tables. To display this tab, choose Tables > Properties from the menu and choose the Weight tab.

352 338 Chapter 15 Figure Table Properties, Weight tab Fields on the Weight tab Weight table using. Select the variable that you want to use to weight the table. Show all numeric variables. Check this box to display all numeric variables in the Weight table using list. Leave the box unchecked to see only variables that have been created specifically for use as weight variables. Add an unweighted base. When working with weighted data, it is good practice to show the unweighted base figures in addition to the weighted base figures. By default, this option is checked, so that an unweighted base is added automatically at the start of each variable in a weighted table. Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Statistics Use the options in the Statistics tab to add statistical tests to your tables. For more information, see the topic Applying Statistical Tests in Chapter 9 on p To display this tab, choose Tables > Properties

353 339 Presenting Your Results from the menu and choose the Statistics tab. Figure Table Properties, Statistics tab Fields on the Statistics tab Net difference Paired preference Column proportions Column means Chi square Fisher exact Significance level Select a significance level for the net difference, paired preference, column proportions, or column means tests. The default level is 5%, indicating a 95% probability that the results are statistically significant. Significance level low If you want to perform the column proportions or column means test at two levels of significance, select a second significance level. The default level is 10%, indicating a 90% probability that the results are statistically significant. Note that the value you select in this field must be larger than that for the first significance level.

354 340 Chapter 15 Small base By default, tests on rows or columns where the base is above the minimum base but below 100 are carried out, but an asterisk (*) appears next to the result to indicate that the base size is small. You can enter a new value for the small base if required. Minimum base By default, tests are not carried out on rows or columns where the base is below 30. Two asterisks (**) are placed in the cell to indicate this. You can change the value for the minimum base if required. Note, though, that for some tests, results obtained with bases of less than 30 may not be statistically valid. Column Test. Choose this button if you want to select the columns to test in a column proportions or column means test, to display the Column Test dialog box. For weighted reports use the effective base (recommended) Select this option if you want IBM SPSS Data Collection Survey Reporter to use the effective base rather than the simple weighted base in statistical tests on weighted tables. This option has no effect on statistical tests run on unweighted tables. Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Apply. Choose this button if you have finished adding statistical tests on this tab, but want to change any settings on the Hide or Sort tabs on the Table Properties dialog box. If your changes result in the addition of any items that can be hidden or sorted (such as the minimum p value column), using the Apply button adds these items to the drop-down lists in the relevant tabs, avoiding the need to close and reopen the dialog box. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Column Test When you add a column proportions or column means test to your tables, you can select the columns that you want to test. Use the options in the Column Test dialog box to select the columns to test. To display this dialog box, choose Tables > Properties from the menu and choose the Statistics tab. Set up your statistics and choose the Column Test button.

355 341 Presenting Your Results Fields on the Column Test dialog box Column IDs. By specifying a character string you can assign each column with a unique character ID that is used for specifying test combinations. ach character in the string is used to allocate the column ID, with a space or period used to indicate that an ID should not be allocated. A character needs to be specified for each of the columns in the table, including BAS columns. For example: "...MF.NG" Note: You cannot include a period or space for hidden columns. Test Columns. nter the column IDs of the table that you want to test, separate using a forward slash character, for example: "A/B/C" This tests all combinations of columns A, B, and C. You can specify separate groupings of columns to test by separating groups of columns with a comma, for example: "A/C/, B/D/F" tests all combinations of columns A, C, and, and all combinations of columns B, D, and F. Note: nsure that the column IDs you specify exist in the table, and that they correspond to valid combinations of columns to test. You can check this by running the test using the same table specification but with the default column selection. Use the Quantum/Quanvert column test formula. nables you to reproduce the IBM SPSS Quantum /IBM SPSS Quanvert formula exactly. For more information, see the topic Statistical Tests Compared to IBM SPSS Quantum and IBM SPSS Quanvert in Chapter 19 on p Table Properties: Hide You can hide rows, columns, or individual cells in which all of the values are zero, or are above or below a certain amount, using the options in the Hide tab. For more information, see the topic Hiding Rows, Columns, and Cells on p To display this tab, choose Tables > Properties from the menu and choose the Hide tab.

356 342 Chapter 15 Figure Table Properties, Hide tab Fields on the Hide tab Hide rows. Check this box to hide rows, then select a condition from the drop-down list and enter a value. For example, select less than and enter a value of 50 to hide rows where values are less than 50. You must then specify the column to use to test the condition in the based on drop-down list. The default is Base Count, which hides rows where the value in the base column is less than 50. If you do not want the hide condition to apply to rows containing means, standard deviation and other special items, check the ignore special elements box. Hide columns. Check this box to hide columns, then select a condition from the drop-down list and enter a value. For example, select less than and enter a value of 50 to hide columns where values are less than 50. You must then specify the row to use to test the condition in the based on drop-down list. The default is Base Count, which hides columns where the value in the base rowislessthan50. If you do not want the hide condition to apply to columns containing means, standard deviation and other special items, check the ignore special elements box. Hide cells. Check this box to hide cells, then select a condition from the drop-down list and enter a value. For example, select less than and enter a value of 50 to hide cells where values are less than 50.

357 343 Presenting Your Results Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Level Use the options in the Level tab to specify the level to use when tabulating hierarchical data. For details of how to tabulate hierarchical data and examples of generating results at different levels, see Tabulating Hierarchical Data. To display this tab, choose Tables > Properties from the menu and choose the Level tab. Figure Table Properties, Level tab Fields on the Level tab Level. This drop-down list box shows the names of the valid levels for your table. Select the level at which you want to tabulate the data. The name of the top level is always Top and the names of the lower levels are the same as the names of the corresponding loops. The drop-down list box lists the names of the valid levels for your table and provides an option to select the default level. The name of the top level is always Top and the names of the lower levels are the same as the names of the corresponding loops.

358 344 Chapter 15 Default level. This is the level at which a table is generated when you do not explicitly specify the generation level. The default level depends on the level of any filters and of all of the variables that are in the table (including any numeric variables included in the cell contents). Note: You cannot apply level settings to multiple tables, as the options available depend on the levels available in individual tables. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Sort Use the options in the Sort tab to specify how you want to sort your tables. For more information, see the topic Sorting Tables on p Note: If there is more than one cell item in the table, the first cell item is always used to test the sort condition. In most tables this is likely to be the Counts cell item. To sort tables based on another cell item, use the Cell Contents tab tomovethecellitemsothatitappearsfirst in the table. To display this tab, select the table you want to sort in the Tables pane, then choose Tables > Properties from the menu and choose the Sort tab. Figure Table Properties, Sort tab

359 345 Presenting Your Results Fields on the Sort tab Sort rows based on. Contains a list of all the columns in the table. Select a column to use to sort the rows of the table. The default is Not sorted (that is, the rows are displayed in the order in which they appear in the variable). You can also choose to sort rows in ascending or descending order. The default is descending order. Sort columns based on. Contains a list of all the rows in the table. Select a row to use to sort the columns of the table. The default is Not sorted (that is, the columns are displayed in the order in which they appear in the variable). You can also choose to sort columns in ascending or descending order. The default is descending order. Note: You cannot apply sort options to multiple tables, as the options available depend on the rows and columns in individual tables. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Header and Footer Use the options in the Header and Footer tab to change the headers and footers that appear in your tables. For more information, see the topic Changing Headers and Footers on p To display this tab, choose Tables > Properties from the menu and choose the Header and Footer tab.

360 346 Chapter 15 Figure Table Properties, Header and Footer tab Fields on the Header and Footer tab Header: Header Title. By default, contains the project description. Center. mpty by default. Left side. By default, contains the table description and filter description. Right side. By default, contains the table number and information on any weighting variable applied to the table and the table level. Footer: Footer Title. mpty by default. Center. mpty by default. Left side. By default, contains the cell contents and information on any statistical tests and hide rules applied to the table, as well as warning messages for statistical tests and explanations of symbols. Right side. mpty by default.

361 347 Presenting Your Results Insert Field. Place the cursor in a header or footer text box and choose this button to open the Field Selection dialog box and select a field to add to the header or footer. Alternatively, you can type the field name directly into the header or footer text box, surrounded by curly brackets {}. For full details of the fields that you can add, see Field Selection. Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Field Selection You can insert a number of fields into table headers and footers to add information about the tables, filters, weighting, data set, date and time of generation, etc. You can use more than one field in a single header or footer, and you can combine the fields with plain text. Use the options in the Field Selection dialog box to select fields to add to a selected header or footer position. To display this dialog box, open either the Header and Footer tab on the Table Properties dialog box: Tables > Properties or the Global Header and Footer dialog box: Tables > Global Headers and Footers Then place the cursor in a header or footer text box and choose the Insert Field button. Fields on the Field Selection Dialog box Field Description Options CDSCName The internal name of the CDSC, \n \p such as mrxmldsc. CellContents The table s cell contents. If \n \p there is more than one, they are separated by line breaks. Context The user context being used, such \n \p as Analysis. CurrentTime The current date and time. By \n \p \s default this is in the long date format for the current language s default regional setting (locale). Use the \s option to use the short date format. DBLocation The name and location of the case data. \n \p

362 348 Chapter 15 Field Description Options DocumentDescription The description of the table \n \p document, such as Analysis of age and education against interest in the various galleries. Filters The descriptions of all of the \e \g \i+ \i- \n \p \t filters, concatenated with the word AND in bold. If the filters are at different levels, details of the levels are shown. If the filter doesn t have a description, its expression is shown. You can use one or more of a number of options. These are described in the table below. LabelType The label type being used, such \n \p as Label. Language The metadata language being \n \p used, such as nglish (United States). Level Thenameofthelevelatwhich \l \n \p \s the table was generated. For example, Person[..].Trip. Use the \l option to use the level s description instead of the name. For example, Overseas trips taken by each person. MDSCName The internal name of the MDSC \n \p being used, such as mrqvdsc. MetaDataLocation The name and location of the \n \p metadata. MetadataVersion The version(s) of the metadata \n \p beingusedintheformofaversion expression, for example, {..}, which indicates a combination of all versions. ProjectDescription The description of the data set, \n \p such as Museum Survey. ProjectName When you are using a CDSC that \n \p supports multiple projects (such as RDB DSC), you can show the name of the project being used, such as short_drinks. Rules The rules defined for the table. \n \p ach rule is separated by a line break. For example, Hide cells where Count equals 0. RunTime The date and time of generation in the current language s default regional setting (locale). By default this is in the long date format. Use the \s optiontouse the short date format. \n \p \s

363 349 Presenting Your Results Field Description Options SideSpec The specification of the side of \l \n \p \s the table. For example, age. Use the \l option for a more friendly version of the side specification in which variable names are replaced by their descriptions. For example, Age of respondent. SortColumn The column by which the \n \p \s table is sorted. For example, Gender{Male}. SortRow The row by which the table \n \p \s is sorted. For example, Age{Base}. Statistics Notes relating to the statistical \i- \n \p tests, separated by a line break. This field should always be used in tables that include a statistical text. For example, Column Proportions: Columns Tested (5%) A/B. If a statistic is invalid, the annotation indicates this. The \i- option suppresses annotations for invalid statistics. TableBase The table s base value. For \n \p example, 602. TableDescription The table description, such \n \p as Age by gender for all respondents. TableName Thenameofthetable,suchas \n \p MyTable. TableNumber The index of the table in the table \g \n \p document, such as 5. TableSpec The table specification, such as \l \n \p \s age * gender. Use the \l option if you want to replace variable names with their descriptions. For example, Age of respondent * Gender of respondent. TopSpec The specification of the top of \l \n \p \s the table. For example, gender. Use the \l option if you want to replace variable names with their descriptions. For example, Gender of respondent. TotalNumberOfTables The total number of tables in the \n \p table document, such as 10. WeightVariable The name of the weighting \l \n \p \s variable. For example, agebalance. Use the \l option if you want to display the weighting variable s description. For example, Weighting factor for age balance.

364 350 Chapter 15 The following additional fields are not available for selection in the Insert Field dialog box, but can be added by typing the syntax directly into the relevant header or footer position, surrounded by curly brackets {}. Field Description Options CellItemSymbols Information about symbols \n \p displayed in the table cells. PopulateWarnings Displays warnings generated \n \p during the generation of statistical tests, for example, if the type of test requested is not valid for the type of table. TableProperty:PropertyName The content of a custom table property. Add the name of the custom property after the colon. To add the text in the Table Notes pane to a table, use the predefined TableNotes custom property. For more information, see the topic Adding Notes to Headers and Footers on p \n \p Field Codes. Choose this button to see a list of the field codes corresponding to the field options. Field Options. The following table describes the field option codes that are available for use with header and footer fields: Option Description \e Always use the filter expression instead of the description. \g (Used with Filters field) Include only global filters (that is, ignore any filters applied directly to the table). \g (Used with TableNumber field) Add hierarchical numbering if the tables are stored in folders; for example, 2.1, 2.1.1, etc. \i+ Include only Interview filters. \i- (Used with Filters field) Include only filters that are not Interview filters. (Used with Statistics field) Suppress annotations for invalid statistics. \l A more friendly version in which variable names are replaced by their descriptions (labels). \n When combining more than one field in a header or footer position, you can use this option to add a conditional line break after the text inserted by the field. The line break will only be inserted if the field inserts some text. \p This option can be used with all fields to add a text prefix. For example, when used with the Filters field, it inserts the text Filters: in front of the details of the filters.

365 351 Presenting Your Results Option Description \s Used with the CurrentTime and RunTime fields, displays the short date format rather than the long date format. Used with the Level, SideSpec, SortColumn, SortRow, TableSpec, TopSpec, and WeightVariable fields, displays the short name of the field instead of the full name. This option is ignored if you use the \l option. \t Include only filters applied directly to the table (that is, ignore global filters). Table Properties: Chart Use the options in the Chart tab to specify the type of chart to display, and to configure other aspects of charts. For more information, see the topic Displaying Results in Charts on p To display this tab, choose Tables > Properties from the menu and choose the Chart tab. Figure Table Properties, Charts tab

366 352 Chapter 15 Fields on the Chart tab Chart type. Select the chart type from the drop-down list. If you want to use a custom chart that you have created in xcel when you export the table to Microsoft Word, xcel, or PowerPoint, type in the name of the custom chart. Chart types that you enter in this tab override the default chart export types that you select in the xport Tables dialog boxes. If you do not want to display a chart for the selected table, type No chart in this field. Chart category elements. You can optionally create charts for individual categories, for individual variables, or for all variables on the table. Select: Per element to create a separate chart for each category in the variable(s). Per variable to create a chart for each variable(s). Per table creates a single chart for all variables on the table. Chart special elements. You can optionally create charts for statistical items (such as the mean, minimum value, standard deviation, etc.). Select: Per element to create a separate chart for each statistical item in each variable. Per variable to create a chart for all statistical items in each variable. Per table creates a single chart for all statistical items in all variables on the table. Base chart on. If you want to base charts on a cell item other than the default, select the cell item from the drop-down list. The cell item must be included in the table. Set as Default. Choose this button if you want the changes you make on this tab to be used as the default settings for all new tables that you create. Restore to Defaults. Choose this button if you want the settings for all selected tables to revert to the default settings. This option restores the settings for all tabs in the Table Properties dialog box, not just the current tab. Table Properties: Default Properties Dialog Box The Table Properties: Default Properties dialog box appears when you choose the Set as Default buttoninatabinthetablepropertiesdialogbox. Usethisdialogboxtochoosewhetheryou want to: change the defaults for all new tables in the current table document. To do this, choose OK. change the defaults for all new tables in the current table document and any new table documents you create. To do this, check the Update document template box and choose OK. Note: The Set as Default option applies the changes only for the currently selected tab in the Table Properties dialog box. To apply the changes for more than one tab, choose the Set as Default button in each tab individually, and follow the same steps.

367 353 Presenting Your Results How the settings in the Table Properties dialog box can be applied Settings in the following tabs can be applied to the current table document and to the template: Cell Contents Display Statistics Header and Footer Chart For information on setting up templates, see Customizing Table Document Templates. Settings in the following tabs can be applied to the current table document, but not to the template: Weight Hide This is because the settings refer to a specific variable or variables that may not be available in another table document. Settings in the following tabs cannot be applied to the current table document or to the template, but only to the currently selected table: Level Sort This is because the options available refer to levels/rows/columns that may not be available in an individual table.

368 Publishing Your Results Chapter 16 When you have finished analyzing your data and applying any formatting you require, you can print your results directly from IBM SPSS Data Collection Survey Reporter to a printer or you can export results to file formats that can be used by other applications. You can export to the following formats: HTML Microsoft xcel Microsoft PowerPoint Microsoft Word Text You can export your tables to a delimited text file (typically a.csv file). You export results using the xport Tables Dialog Box. When you first use an export format, Survey Reporter downloads and installs a component on your local machine for that format. Generally this is quick and does not cause a problem. However, it requires you to have administrator rights on your local machine. When you subsequently export to the same format, Survey Reporter detects that the component has already been downloaded and does not download it again. Note that you cannot export data from Survey Reporter when working with a project opened from the IBM SPSS Data Collection Interviewer Server Administration server (sometimes known as the Accessories server). Data export is only supported for projects opened from the local machine. Interviewer Server Administration provides its own xport Data feature. Printing Results You can print the results you create directly from IBM SPSS Data Collection Survey Reporter, or you can export them to other applications. Printing directly from Survey Reporter prints the contents of the Results pane to the selected printer. This is useful if you want a quick printout of your results. The formatting of the printout is equivalent to that provided by the HTML export option. For completed reports, you may prefer to export results to one of the export formats available, which provide alternative formatting options. For further information on exporting results to other applications, see xporting Results. If you have not generated the results for a table, only the structure of the table is printed. Charts are not printed at all if you have not generated results. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

369 355 Publishing Your Results To select the tables to print In the Tables pane: to print a single table, select that table in the list. to print a number of tables, use Shift+click or Ctrl+click to select them. to print all tables in a table document, select the table document at the top of the Tables pane, or place the cursor anywhere in the Tables pane and press Ctrl+A. If necessary, press F5 to generate results for the selected tables. To preview the printout From the menu, choose File > Print Preview > Results or press Alt+F, V, R. The Print preview dialog box appears. You can use this to check whether the printout is as you require it and to see how many pages it contains. To print results Choose the Print button in the Print Preview dialog box, or from the menu, choose File>Print>Results or press Ctrl+P. Select the printer that you want to use. If required, select the pages to print using the Page Range options. Set any printer-specific options as required. Choose Print. xporting Results You can export the results from all tables in the table document (.mtd file), or from selected tables. To export results from all tables: From the menu, choose: File > xport > Tables The xports dialog box appears. In the xport To drop-down list box, select the export format, for example, HTML xport. The remainder of the fields in this window are optional, and reflect the export format you have selected. Select any other options you require. For more information, see the topic xport Tables DialogBoxonp. 357.

370 356 Chapter 16 Choose xport. To export results from selected tables: Click a table in the Tables pane to select it. To select a number of tables, use Shift+click or Ctrl+click. From the menu, choose: File > xport > Tables The xports dialog box appears. In the xport To drop-down list box, select the export format, for example, HTML xport. Choose Selected tables. The remainder of the fields in this window are optional, and reflect the export format you have selected. Select any other options you require. For more information, see the topic xport Tables DialogBoxonp Choose xport. The results are exported to the appropriate format in the default location. nabling security access for Microsoft xcel, Word, and PowerPoint exports Security settings in Microsoft xcel, Word, or PowerPoint may prevent you from exporting to these applications. If this occurs, you can enable the export to run by changing a security setting in Microsoft xcel, Word, or PowerPoint. If you need to change the setting on your machine, a message will inform you of this. Follow the instructions below to change the settings. If you are in doubt about whether changing security settings is permitted by your organization, please contact your system administrator. Note: nsure that you have the latest Microsoft Office service pack installed. To check this, choose the Check for Updates option on the Microsoft xcel Help menu to display the Microsoft Office Downloads page, where you can download the latest service pack. Microsoft Office 2007 or above Note: Setting the security options in one program does not set them in the other. You may need to follow these steps for xcel, Word, and PowerPoint depending on your existing security settings. In Microsoft Office 2007, macro security settings are located in the Trust Center. nsure that IBM SPSS Data Collection Survey Reporter and all Microsoft Office applications are closed. Open xcel, Word, or PowerPoint. Click the Microsoft Office button.

371 357 Publishing Your Results Click the xcel Options, Word Options, orpowerpoint Options button. Click Trust Center > Trust Center Settings In xcel, additionally click Macro Settings. Select the Trust access to the VBA project object model check box. Click OK to apply the setting. Close xcel, Word, or PowerPoint. For more information, see nable or disable macros in Office documents ( at xport Tables Dialog Box You use the xports dialog box when you want to export your results to other formats. To open the xports dialog box, choose the following options from the menu: File > xport Tables Figure 16-1 xports dialog box Fields on the xport Tables dialog box xport: All tables. Select if you want to export all of the tables in this table document. Selected tables. Select if you want to export only those tables that you have selected in the Tables pane. You can select multiple tables using Shift+click or Ctrl+click. xport tables to. Select the export option you require. IBM SPSS Data Collection Survey Reporter comes with the following options: HTML. This option enables you to export tables and charts to HTML. The HTML export requires Microsoft Office Web Components (OWC) version 10 or later to create charts. However, this is not necessary if you want to export only tables.

372 358 Chapter 16 Microsoft xcel. This option enables you to export tables and charts to Microsoft xcel. The export creates output in Microsoft xcel that is suitable for printing and easy to manipulate. To use this option, you need to have Microsoft Office 2007 or later installed on your desktop machine. Microsoft PowerPoint. This option enables you to export tables to Microsoft PowerPoint as charts (by default) and tables. ach table or chart is created on a separate Microsoft PowerPoint slide. To use this option, you need to have Microsoft Office 2007 or later installed on your desktop machine. Considering that PowerPoint xport relies on the Microsoft xcel component, you should close all xcel files (to avoid an invalid export result) prior to starting the export. Microsoft Word. This option enables you to export tables and charts to Microsoft Word. The export has been designed to create output in Microsoft Word that looks good, is suitable for printing, and easy to customize. To use this option, you need to have Microsoft Office 2007 or later installed. Text file. This option enables you to export tables to a delimited text file (typically a.csv file). Additional options are available depending on which type of export you select: HTML xport options Microsoft xcel xport options Microsoft PowerPoint xport options Microsoft Word xport options Text xport options HTML xports When you select HTML in the xport Tables dialog box, a number of additional options become available.

373 359 Publishing Your Results Figure 16-2 xport Tables dialog box after choosing the HTML option Fields on the xport Tables dialog box for HTML exports Include. Choose whether to create tables only, charts only, or both tables and charts, and whether to display the chart or the table first. For details of the way in which you can display data in charts, see Displaying Results in Charts. Note: The HTML export requires Microsoft Office Web Components (OWC) version 10 or later to create charts. However, this is not necessary if you want to export only tables. Default chart type. If you have chosen to export charts, select a chart type from the drop-down list. Note: The chart type you select is used only if you have not specified a chart type for a table using the Table Properties dialog box. Presentation. Select the style sheet you want to use to format the HTML output. You can choose from any of the built-in style sheets. If you have created any custom style sheets and added them to the styles folder, they also appear in the list. For more information, see the topic Customizing the Format of Your Results in Chapter 18 on p HTML layout. This controls the layout style. Choose from: Single document. All of the tables and/or charts are exported to one HTML document, which has a table of contents at the top. By default the tables, charts, or table and chart pairs are separated by a printing page break.

374 360 Chapter 16 Figure 16-3 Single document layout style Table of Contents. The table of contents and each table and/or chart are exported to a separate HTML Document. You can navigate the pages using the table of contents. Figure 16-4 Table of contents layout style Frame Table of Contents. ach table, chart, or table and chart pair are exported to a separate document with the table of contents visible in a separate frame on the left side.

375 361 Publishing Your Results Figure 16-5 Frame Table of Contents layout style Launch browser after export. Select if you want IBM SPSS Data Collection Survey Reporter to automatically display the exported tables in your default browser. Save to file. Check this box and enter a name and location for the output file, or choose the Browse button to browse to the folder where you want to save it. If you do not specify a save location, and the Launch after export option is also not selected, you are prompted to either launch the associated application or select a save location. Advanced HTML xport Properties Choose the Advanced button to view or edit the Advanced HTML xport Properties dialog box. Display Properties: Variable. Choose whether to use variable names or the more friendly descriptions for the variable texts in the tables. Category. Choose whether to use category names or the more friendly descriptions for the row and column headings in the tables. Title. Check this box to include the project description as the title in the HTML output. Logo. Select this option if you want a logo to be inserted in the top left corner of the HTML file. The IBM Corp. logo is provided for use as a default logo, but this can easily be replaced with any other suitable logo. You do this by including your own logo as a PNG file called logo.png in the output folder. The HTML export will not overwrite a file of this name. Headers and footers. Select this option if you want to export the headers and footers that have been defined for the table.

376 362 Chapter 16 Variable and category images. Select this option if you want to export images associated with table rows and columns. These may be images that were specified when the data was created using IBM SPSS Data Collection Interviewer Server, or they may be images that were added to your tables using IBM SPSS Data Collection Base Professional Tables Option. Horizontal variable text in side headings. Select this option to display text in the side headings horizontally, or deselect to display text vertically. Chart Properties: Chart series. Choose whether you want the table rows or columns to form the chart series. If you select the Chart category elements or Chart special elements box, ensure that the orientation of the categories or special items (in rows or columns) corresponds to the setting entered here. For example, to create a chart for a mean that appears on the top of a table, choose as columns. Chart category elements. You can optionally create charts for individual categories, for individual variables, or for all variables on the table. Select: Per element to create a separate chart for each category in the variable(s). Per variable to create a chart for each variable(s). Per table creates a single chart for all variables on the table. Chart special elements. You can optionally create charts for statistical items (such as the mean, minimum value, standard deviation, etc.). Select: Per element to create a separate chart for each statistical item in each variable. Per variable to create a chart for all statistical items in each variable. Per table creates a single chart for all statistical items in all variables on the table. Base chart on. If you want to base charts on a cell item other than the default, select the cell item from the drop-down list. The cell item must be included in the table. Display series base. Select this option to display the base for the chart series in the legend for the chart. Display base for last series category. Check this box to display the base for the last data point in the chart legend. This option is applicable only when charting special items. If the count cell item is present, this is used. If not, the unweighted count cell item is used. Chart percentages using scale of 0 to 100%. Check this box if you want percentages to be charted on a scale of 0 to 100%. If this option is not selected, the scale is based on the biggest value in the chart. HTML Properties: Use formatted labels. Select this option if you want to use HTML formatting in variable and category descriptions in a similar way to using HTML formatting in the headers and footers. The same set of HTML tags are supported and as in headers and footers, the HTML must be well-formed. For more information, see the topic HTML Formatting for Headers and Footers in

377 363 Publishing Your Results Chapter 15 on p Typically you set up the formatting in the dit Variable dialog box before exporting. If you export to any of the other formats (or to HTML without using this option), any HTML tags in the variable or category descriptions will appear as plain text. Note that using this option may make the export run a little more slowly. For more information, see the topic Using HTML Formatting in Category Descriptions on p mbed style sheet. Select this option if you want to embed the style sheet within the HTML file. This is useful when you want to distribute the HTML output, for example, by . Insert printing page breaks. Select this option if you want to add a printing page break between tables when using the Single Document layout style. Note that this option does not insert a printing page break between tables and charts. Microsoft xcel xports When you select Microsoft xcel in the xport Tables dialog box, a number of additional options become available. To use this option, you need to have Microsoft Office 2007 or later. Note: You may need to set an access security setting in xcel before you can run the export. If this applies to your machine, IBM SPSS Data Collection Survey Reporter will display a message telling you this. For step-by-step instructions on setting the security setting, see nabling security access for Microsoft xcel, Word, and PowerPoint exports. Figure 16-6 xport Tables dialog box after choosing the Microsoft xcel option Fields on the xport Tables dialog box for Microsoft xcel exports Display charts. You can optionally choose to export data in chart format. The export creates each chart on a separate worksheet immediately following the worksheet that contains the related table. Select a chart type from the drop-down list. To use a custom chart that you have created in xcel, type in the name of the custom chart. To specify a chart template (xcel 2007 only),

378 364 Chapter 16 click Browse... to select the desired file. For details of the way in which you can display data in charts, see Displaying Results in Charts. Note: The chart type you select is used only if you have not specified a chart type for a table using the Table Properties dialog box. The xcel worksheets that contain the tables are called T1, T2, T3, etc. The worksheets that contain charts are called T1_ch, T2_ch, T3_ch, etc.wheret1, T2, andt3 are the names of the worksheets containing the tables to which they relate. Hide xcel during export. Select this option to hide xcel during the export. This makes the export faster. Launch xcel after export. Select if you want Survey Reporter to automatically launch xcel and open the file that contains the exported table(s) when the export is complete. Save to file. Check this box and enter a name and location for the output file, or choose the Browse button to browse to the folder where you want to save it. If you do not specify a save location, and the Launch after export option is also not selected, you are prompted to either launch the associated application or select a save location. Advanced xcel xport Properties Choose the Advanced button to view or edit the Advanced xcel xport Properties dialog box. Display Properties: Variable. Choose whether to use variable names or the more friendly descriptions for the variable texts in the tables. Category. Choose whether to use category names or the more friendly descriptions for the row and column headings in the tables. Borders. Select this option if you want the tables to have borders in xcel. Headers and footers. Select this option if you want to export the headers and footers that have been defined for the table. When this option is selected, all of the headers and footers are displayed left aligned, regardless of the positions definedintheheaderandfooterdialogbox.thishasthe advantage that they are easily visible in a wide table. Formatting for headers and footers. Select this option if you want headers and footers to be copied to the clipboard as formatted HTML. When this property is set to False, the annotation is copied as plain text, so that all tags (except <br/>) appear in the xcel output. Set this option to False in a server environment. Base values. This option controls the display of base rows and columns. If you leave this box blank, all rows or columns containing bases are suppressed for all tables, so that they are not displayed in the output file. If you check the box, rows and columns are displayed or hidden according to what is specified in the definition for each table.

379 365 Publishing Your Results Chart options: Chart series. Choose whether you want the table rows or columns to form the chart series. If you select the Chart category elements or Chart special elements box, ensure that the orientation of the categories or special items (in rows or columns) corresponds to the setting entered here. For example, to create a chart for a mean that appears on the top of a table, choose as columns. Chart category elements. You can optionally create charts for individual categories, for individual variables, or for all variables on the table. Select: Per element to create a separate chart for each category in the variable(s). Per variable to create a chart for each variable(s). Per table creates a single chart for all variables on the table. Chart special elements. You can optionally create charts for statistical items (such as the mean, minimum value, standard deviation, etc.). Select: Per element to create a separate chart for each statistical item in each variable. Per variable to create a chart for all statistical items in each variable. Per table creates a single chart for all statistical items in all variables on the table. Base chart on. If you want to base charts on a cell item other than the default, select the cell item from the drop-down list. The cell item must be included in the table. Display series base. Select this option to display the base for the chart series in the legend for the chart. Display base for last series category. Check this box to display the base for the last data point in the chart legend. This option is applicable only when charting special items. If the count cell item is present, this is used. If not, the unweighted count cell item is used. Display column statistics results. Displays the column IDs for a column proportions or column means test next to the category descriptions, and adds the column proportions test results to the chart above the relevant columns. Chart percentages using scale of 0 to 100%. Check this box if you want percentages to be charted on a scale of 0 to 100%. If this option is not selected, the scale is based on the biggest value in the chart. Worksheet options: Use xcel styles. Select this option if you want to use styles to control the formatting. By default, the exported tables will look the same whether you use styles or not. However, styles make it easytoalterthelookofyourtablesandapplystandardformattingtomultipletables. Ifyou want to use xcel to manipulate the data in the tables rather than printing them, you may prefer to export without using styles. For more information, see the topic xporting Tables Using Microsoft xcel Styles on p. 374.

380 366 Chapter 16 Printing: This option controls the print option that will be selected in the xcel file. Note this does not affect how the tables appear in xcel. It affects how large tables appear when they are printed. The options are: Repeat axes. This selects the xcel print option to repeat title rows and columns on every page so that when a table is split between more than one printed page, the table row and column headings are repeated on every page. Fit to page. This selects the adjust to fit on one page xcel printing option. None. This does not select any printing options in xcel. Show column statistics results with first cell item. This option controls the display of significance letters for column proportion and column mean tests. If you leave this box blank, the significance letters are shown in cells after the cell items, as in the Results pane. If you check this box, significance letters are shown in the same xcel cell as the first cell item. Note that charts are not produced for tables with column proportion results shown with the firstcellitem. Create a separate table for each cell item. Select this option if you want each type of cell contents to appear in a separate table (all of the tables are on the same worksheet). This is useful if you want to perform calculations on the output or set up your own charts in xcel. Wrap description text. Select this option if you want to wrap long descriptions onto the next line. Auto-fit column widths. Select this option if you want to automatically change the width of the table columns to accommodate the width of the text. By default, this option is not enabled. Microsoft PowerPoint xports When you select the Microsoft PowerPoint option in the xport Tables dialog box, a number of additional options become available. To use this option, you need to have Microsoft Office 2007 or later installed on your desktop machine. Considering that PowerPoint xport relies on the Microsoft xcel component, you should close all xcel files (to avoid an invalid export result) prior to starting the export. Note that by default, tables are exported to PowerPoint as charts.

381 367 Publishing Your Results Figure 16-7 xport Tables dialog box after choosing the Microsoft PowerPoint option Fields on the xport Tables dialog box for Microsoft PowerPoint exports Include. Use this option to specify whether the export should create charts only, tables only, or both tables and charts, and whether the chart or the table should be shown first. Note that the tables and charts are created using Microsoft xcel, so you need to have both PowerPoint and xcel installed to be able to use these options.for details of the way in which you can display data in charts, see Displaying Results in Charts. Default chart type. Select a chart type from the drop-down list. If you want to use a custom chart that you have created in xcel, type in the name of the custom chart. Note: The chart type you select is used only if you have not specified a chart type for a table using the Table Properties dialog box. Hide PowerPoint during export. Select this option to hide PowerPoint during the export. This makes the export faster. Launch PowerPoint after export. Select if you want IBM SPSS Data Collection Survey Reporter to automatically launch PowerPoint and open the file that contains the exported table(s). Apply PowerPoint template. If you want to use a PowerPoint template other than the default, choose the Browse button and select another template to attach to the PowerPoint file. By default, PowerPoint templates are stored in subfolders under a Microsoft Office templates folder, for example, C:\Program Files\Microsoft Office\Templates\Presentation Designs and have the file extension.pot.

382 368 Chapter 16 Save to file. Check this box and enter a name and location for the output file, or choose the Browse button to browse to the folder where you want to save it. If you do not specify a save location, and the Launch after export option is also not selected, you are prompted to either launch the associated application or select a save location. Advanced PowerPoint xport Properties Choose the Advanced button to view or edit the Advanced PowerPoint xport Properties dialog box. Display Properties: Variable. Choose whether to use variable names or the more friendly descriptions for the variable texts in the tables. Category. Choose whether to use category names or the more friendly descriptions for the row and column headings in the tables. Title slide. When you export to PowerPoint a title slide is created automatically. If you do not want to include the title slide, deselect this box. Headers. Select this option to include any headers attached to the table in the PowerPoint slides. Footers. Select this option to include any footers attached to the table in the PowerPoint slides. Chart Properties: Chart series. Choose whether you want the table rows or columns to form the chart series. If you select the Chart category elements or Chart special elements box, ensure that the orientation of the categories or special items (in rows or columns) corresponds to the setting entered here. For example, to create a chart for a mean that appears on the top of a table, choose as columns. Chart category elements. You can optionally create charts for individual categories, for individual variables, or for all variables on the table. Select: Per element to create a separate chart for each category in the variable(s). Per variable to create a chart for each variable(s). Per table creates a single chart for all variables on the table. Chart special elements. You can optionally create charts for statistical items (such as the mean, minimum value, standard deviation, etc.). Select: Per element to create a separate chart for each statistical item in each variable. Per variable to create a chart for all statistical items in each variable. Per table creates a single chart for all statistical items in all variables on the table. Base chart on. If you want to base charts on a cell item other than the default, select the cell item from the drop-down list. The cell item must be included in the table.

383 369 Publishing Your Results Display series base. Select this option to display the base for the chart series in the legend for the chart. Display base for last series category. Check this box to display the base for the last data point in the chart legend. This option is applicable only when charting special items. If the count cell item is present, this is used. If not, the unweighted count cell item is used. Display column statistics results. Displays the column IDs for a column proportions or column means test next to the category descriptions, and adds the column proportions test results to the chart above the relevant columns. Chart percentages using scale of 0 to 100%. Check this box if you want percentages to be charted on a scale of 0 to 100%. If this option is not selected, the scale is based on the biggest value in the chart. Table Properties: Borders. Select this option if you want tables to have borders in PowerPoint. Wrap description text. Select this option if you want to wrap long descriptions onto the next line. Auto-fit column widths. Select this option if you want to automatically change the width of the table columns to accommodate the width of the text. By default, this option is not enabled. Microsoft Word xports When you select Microsoft Word in the xport Tables dialog box, a number of additional options become available. Note that to use this option, you need to have Microsoft Office 2007 or later installedonyourdesktopmachine.

384 370 Chapter 16 Figure 16-8 xport Tables dialog box after choosing the Microsoft Word option Fields on the xport Tables dialog box for Microsoft Word exports Include. Use this option to specify whether the export should create tables only, charts only, or both tables and charts, and whether the chart or the table should be shown first. Note that the charts are created using Microsoft xcel, so you need to have both Word and xcel installed to be able to use the chart options.for details of the way in which you can display data in charts, see Displaying Results in Charts. Default chart type. If you have chosen to export charts, select a chart type from the drop-down list. If you want to use a custom chart that you have created in xcel, type in the name of the custom chart. Note: The chart type you select is used only if you have not specified a chart type for a table using the Table Properties dialog box. Hide Word during export. Select this option to hide Word during the export. This makes the export run faster. However, this option is not recommended if you are using Word 2000, because it can lead to the export failing. Launch Word after export. Select if you want IBM SPSS Data Collection Survey Reporter to automatically launch Word and open the file that contains the exported table(s). Note: You may need to set an access security setting in Word before you can run the export. If this applies to your machine, Survey Reporter will display a message telling you this. For step-by-step instructions on setting the security setting, see nabling security access for Microsoft xcel, Word, and PowerPoint exports.

385 371 Publishing Your Results Apply Word template. nter the name and location of a Word template to use, or choose the Browse button to browse to the folder containing the template. Leave this text box blank if you want to use the default template. For more information, see the topic Formatting the Output in Microsoft Word on p Save to file. Check this box and enter a name and location for the output file, or choose the Browse button to browse to the folder where you want to save it. If you do not specify a save location, and the Launch after export option is also not selected, you are prompted to either launch the associated application or select a save location. Advanced Word xport Properties Choose the Advanced button to view or edit the Advanced Word xport Properties dialog box. Display Properties: Variable. Choose whether to use variable names or the more friendly descriptions for the variable texts in the tables. Category. Choose whether to use category names or the more friendly descriptions for the row and column headings in the tables. Table of Contents. Select this option if you want the export to create a table of contents. By default, the table of contents is generated from the text in the left header position. This works best when you display the table description (and nothing else) in the left header position. For more information, see the topic Changing the Headers and Footers Used in the Table of Contents on p Borders. Select this option if you want the tables to have borders. Headers and footers. Select this option if you want to export the headers and footers that have been defined for the table. When this option is selected, the headers and footers are positioned on the page above and below the table to which they relate. Note that they are not positioned using the Word header and footer feature. Variable and category images. Select this option if you want to export images associated with table rows and columns. These may be images that were specified when the data was created using IBM SPSS Data Collection Interviewer Server, or they may be images that were added to your tables using IBM SPSS Data Collection Base Professional Tables Option. Chart Properties: Chart series. Choose whether you want the table rows or columns to form the chart series. If you select the Chart category elements or Chart special elements box, ensure that the orientation of the categories or special items (in rows or columns) corresponds to the setting entered here. For example, to create a chart for a mean that appears on the top of a table, choose as columns.

386 372 Chapter 16 Chart category elements. You can optionally create charts for individual categories, for individual variables, or for all variables on the table. Select: Per element to create a separate chart for each category in the variable(s). Per variable to create a chart for each variable(s). Per table creates a single chart for all variables on the table. Chart special elements. You can optionally create charts for statistical items (such as the mean, minimum value, standard deviation, etc.). Select: Per element to create a separate chart for each statistical item in each variable. Per variable to create a chart for all statistical items in each variable. Per table creates a single chart for all statistical items in all variables on the table. Base chart on. If you want to base charts on a cell item other than the default, select the cell item from the drop-down list. The cell item must be included in the table. Display series base. Select this option to display the base for the chart series in the legend for the chart. Display base for last series category. Check this box to display the base for the last data point in the chart legend. This option is applicable only when charting special items. If the count cell item is present, this is used. If not, the unweighted count cell item is used. Display column statistics results. Displays the column IDs for a column proportions or column means test next to the category descriptions, and adds the column proportions test results to the chart above the relevant columns. Chart percentages using scale of 0 to 100%. Check this box if you want percentages to be charted on a scale of 0 to 100%. If this option is not selected, the scale isbasedonthebiggestvaluein the chart. Page Properties: Repeat heading rows. This option affects tables that are too long to fit on one page and need to be split across two or more pages. Select this option if you want the table column headings to be repeated on every page. Deselect this option if you want the column headings to appear on the first page only. Insert page break after each table. Select this option if you want a page break to be inserted between the exported tables. Note that this option does not insert a page break between tables and charts. Text xports When you select Text in the xport Tables dialog box, a number of additional options become available.

387 373 Publishing Your Results Figure 16-9 xport Tables dialog box after choosing the Text option Fields on the xport Tables dialog box for Text exports Launch text viewer after export. Select if you want IBM SPSS Data Collection Survey Reporter to automatically launch the file in its default application (typically this is Microsoft xcel for a.csv file and Notepad for a.txt file, but it will depend on what you have installed and the setup on your machine). Save to file. Check this box and enter a name and location for the output file, or choose the Browse button to browse to the folder where you want to save it. If you do not specify a save location, and the Launch after export option is also not selected, you are prompted to either launch the associated application or select a save location. Advanced Text xport Properties Choose the Advanced button to view or edit the Advanced Text xport Properties dialog box. Display Properties: Variable. Choose whether to use variable names or the more friendly descriptions for the variable texts in the tables. Category. Choose whether to use category names or the more friendly descriptions for the row and column headings in the tables. Headers and footers. Select this option if you want to export the headers and footers that have been defined for the tables. Formatting Properties: Table delimiter. Select the character you want to use to separate the tables. (This must be different from the Field Delimiter character.) The default is a form feed character.

388 374 Chapter 16 Field delimiter. Select the character you want to use to separate the fields. The default character is a comma (,). xporting Tables Using Microsoft xcel Styles When you export tables to Microsoft xcel, you can choose whether to use styles to control the formatting. By default, the exported tables will look the same whether you use styles or not. However, styles make it easy to alter the look of your tables and apply standard formatting to multiple tables. If you want to use xcel to manipulate the data in the tables rather than printing them, you may prefer to export without using styles. To use styles, choose the Use xcel styles option in the xcel xports Dialog Box. In xcel, each style has a name and defines a combination of formatting characteristics, such as font, font size, color, and emphasis, and indentation. When you apply a specifiedstyletoanitem, all of the formatting that is stored in that style is automatically applied to the item. By changing the formatting defined for a style, you can quickly change the formatting of all of the items to which the style has been applied. The following table lists the styles that are used by the xcel export. Style Type Style Name Description Annotations Footer Used to format header and footer Header annotations. Variabletext lementtext VariableTextTop VariableTextSide lementtexttop lementtextside Used to format variable names or descriptions in the table column headers. Used to format category names or descriptions in the table row headers. Cell values Values Used to format cell contents. The following diagram shows the styles used to format the various texts in a table.

389 375 Publishing Your Results Figure Styles applied to texts in a table Note that the export does not apply borders to the exported tables using styles. However, you can switch borders on and off using the Display borders option in the xports dialog box. Sometimes you may want to apply a standard formatting to your exported tables for example, because you have a house style. You can do this in two steps: xport your tables using the Use xcel styles option. In xcel, adjust the formatting of the xcel xport styles shown in the table above to suit your requirements. Save the xcel file. xport your tables using the Use xcel styles option. Open the master document you set up in step 1. Open the newly exported xcel workbook if not already open, and then choose Style on the Format menu. Click Merge. In the Merge styles dialog box, double-click the master document that contains the formatting you want to copy. Choose Yes when you are prompted whether you want to merge the styles with the same names.

390 376 Chapter 16 Headers and Footers All of the headers and footers are displayed left aligned, regardless of the positions selected in the Header and Footer dialog box. This has the advantage that in a wide table all of the headers and footers are easily visible. The following table shows the order in which the headers and footers are presented. Headers Title Header Left Header Center Header Right Header Footers Title Footer Left Footer Center Footer Right Footer You can suppress the headers and footers from the export by deselecting the Display headers and footers export option. xporting Charts Using Microsoft xcel Custom Chart Types When you export charts to Microsoft xcel, PowerPoint, or Word, you can optionally export the charts to a user-defined custom chart type you have set up using xcel. This means you can set up a chart in xcel and configure the type of chart, the placement of the chart legend, the colors used, and so on, to any format available in xcel, and then enter the name of this chart type in the xport dialog box when you export from IBM SPSS Data Collection Survey Reporter. Note: This documentation provides information on making xcel custom chart types available for use with Survey Reporter. It does not explain how to create charts in xcel. For details, see your Microsoft xcel user documentation. These steps may vary depending on the version of xcel you are using. To create a custom chart type in xcel Note: When using a custom pie chart or template, ChartCategorylements must be set to Per element. Refer to the topic Microsoft xcel Tables xport Properties in the IBM SPSS Data Collection Developer Library for more information. If you want to base the style of your custom chart type on a chart available in Survey Reporter, export a sample table from Survey Reporter to xcel, checking the Display charts check box and selecting the appropriate chart type. Alternatively, you may prefer to begin by creating a new chart in Microsoft xcel. Note that some chart types require the data to be organized in a particular format. For details about creating charts in xcel and the ways in which different chart types display data, see your Microsoft xcel user documentation. In xcel, double-click an area of the chart to display the formatting dialog box for that area, and adjust the settings to your requirements. For example, if you double-click a chart legend, the Format Legend dialog box appears and enables you to change the patterns, font, and placement of the legend.

391 377 Publishing Your Results When you finish formatting the chart, select the whole chart area (selection handles appear around the edges of the area) and choose Chart > Chart Type from the xcel menu. In the Chart Type dialog box, select the Custom Types tab. Click the User-defined option button, then click Add to display the Add Custom Chart Type dialog box. nter a name and description for the chart type and click OK. This creates the new custom chart type. You can now use this chart type when exporting from Survey Reporter to xcel, PowerPoint, or Word. For more information, see the topic Displaying a Chart in Chapter 15 on p To share custom chart types All user-defined custom chart types you create in xcel are stored in a file named xlusrgal.xls in the following location: C:\Documents and Settings\username\Application Data\Microsoft\xcel\Xlusrgal.xls Note: If you are using xcel 2007, the file is saved as a.crtx file in the following location: C:\Documents and Settings\username\Application Data\Microsoft\Templates\Charts If you want to share chart types you have created, you can send other users this file, together with a note of the exact name of the custom chart(s). To use the custom charts, they can either: Place the file in their own user folder, replacing any existing file of the same name. This is the easiest method if they have not created or do not wish to keep their own custom charts. Open the file in xcel. ach custom chart type is displayed in a separate worksheet. They can then select each chart in turn and save it as a user-defined custom chart type as described above. This method is useful for anyone who has already created their own custom charts and doesnotwishtolosethem. Using HTML Formatting in Category Descriptions You can add HTML formatting to variable and category descriptions (labels). This is similar to adding HTML formatting to headers and footers. The same set of HTML tags are supported and, like headers and footers, the HTML must be well-formed. For more information, see the topic HTML Formatting for Headers and Footers in Chapter 15 on p Although it is generally preferable to format the descriptions using the style sheet wherever possible, you can use this feature to change fonts and colors for variable and category descriptions, or to add graphics to the row and column headings.

392 378 Chapter 16 Formatted descriptions are supported in the HTML export only. To display the formatted labels correctly, you must select the Use Formatted Labels option when you export to HTML. If you export to any of the other formats (or if you export to HTML without selecting this option), any HTML tags in the variable or category descriptions will appear as plain text. HTML formatting is not supported in charts. To add HTML formatting, you need to edit the category descriptions using the dit Variable dialog box. For example, here is a table showing the gender variable on the side and the before variable on the top. The color of the text has been changed by adding the <font> tag to the descriptions and using the color attribute to specify the color of the text. The symbols have been added by using the face attribute to change the font to Wingdings 2 and Webdings, and changing the text of the description to a single character that produces the appropriate symbol when displayed in those fonts. Figure Tablewithformattinginlabels The following table shows how the descriptions were edited. Variable Name Category Name Description (label) Before <font color= #C0000 >Visited Before</font> Base <font color= #C0000 >Base</font> Yes <b><font face= Wingdings 2 color= #C0000 size= 3 >P</font></b> No <b><font face= Webdings color= #C0000 size= 2 >r</font></b> Gender <font color= #C0000 >Gender</font> Base <font color= #C0000 >Base</font> Male <font color= #C0000 >Male</font> Female <font color= #C0000 >Female</font>

393 379 Publishing Your Results Adding graphics You can also use HTML formatting to add graphics to category row and column headings using the <img> tag. For example, you can display logos or pictures of products in addition to (or instead of) the category descriptions. Here is a table that illustrates this. Figure Table with graphics in category descriptions The table has the interest variable on the side of the table. The descriptions of seven of the categories in the interest variable have been changed to images as shown in the following table. The other categories have been deleted. Category Name Dinosaurs Fish_and_reptiles Fossils Birds Insects Whales Botany Description (label) <img src= C:\Images\Dinosaur.png alt= Dinosaurs /> <img src= C:\Images\Fish.png alt= Fish and reptiles /> <img src= C:\Images\Fossil.png alt= Fossils /> <img src= C:\Images\Bird.png alt= Birds /> <img src= C:\Images\Insects.png alt= Insects /> <img src= C:\Images\Whales.png alt= Whales /> <img src= C:\Images\Botany.png alt= Botany /> Notice that the alt attribute has been added so that the category description is displayed when someone points with their mouse at the pictures in the HTML output. For the images to be displayed correctly in the HTML output, they must exist in the specified locations on the output machine.

394 380 Chapter 16 Formatting the Output in Microsoft Word When you export your tables to Microsoft Word, the tables are placed one after the other in a single Word document. The exported tables are inserted into Word tables using the Automatically resize to fit contents option. This means that the Word export is not suitable for extremely wide tables that cannot be displayed properly in the available page width. (Note that you can use a custom template to set the page orientation to landscape.) Long tables do not pose the same problem, because they can be split across multiple pages when necessary. You can select the Repeat Heading Rows option in the Word xports dialog box if you want the table column headings to be repeated on each page when this happens. Similarly, the Display Borders option enables you to specify whether or not the tables should have borders. Formatting of the text is controlled using Word templates and styles. For further information, see: Working with Microsoft Word Templates Working with Microsoft Word Styles Working with Microsoft Word Templates All Microsoft Word documents are based on templates. Templates apply to an entire document and determine its basic structure, including the default page size and orientation, margins, styles, and page headers and footers (not to be confused with table headers and footers). Templates can also include logos and standard text that are to be included in the document before or after the tables, etc. Templates help you standardize designs and can save you time, because they enable youtocreateaformattingschemeandapplyittomultipleexports. There are two basic types of templates in Word global templates and document templates. Global templates are available to all documents, whereas a document template contains settings that are available only to documents that are based on, or attached to, it. IBM SPSS Data Collection Survey Reporter uses a document template to format the exported tables. When you export your tables, the Word document is formatted using a built-in template called WordTemplate.dot, unless you specify a different template. The first time you run an export to a new location using the built-in template, the export saves the default WordTemplate.dot template in the output folder. If you do not specify a destination folder and you are using the built-in template, the template is written to the default Word templates folder, if not already present there. When you subsequently export to the same location, the template is not overwritten. This means that you can make changes to the template and your changes will be preserved the next timeyouexporttothesamelocation. Alternatively, you can save your template in another location, such as the main Office templates folder, and explicitly select the template when you run an export. Typically you would first run an export using the built-in template to get a copy of the default WordTemplate.dot template and then use this as a starting point for creating your own templates. You can subsequently change the template that is attached to a document by using the Templates and Add-Ins option on the Word Tools menu. When you attach a template, select Automatically update document styles in the Word Templates and Add-Ins dialog box. This updates all of the styles in the document with the styles in the template. Note that changing the template in

395 381 Publishing Your Results this way does not change the position of the various items or the page layout of the document (for example, the margin settings and the page headers and footers are not changed). The default template contains the following: Bookmarks. These define the position of the tables, survey name and description, and table of contents. For example, you can specify that the table of contents is to appear after the tables by positioning the bookmarks appropriately. Styles. ach part of the table is mapped to its own style in Word. You can change the appearance of the various parts of the table by changing the styles. For a complete list of the default styles, see The Default Microsoft Word xport Styles. The default styles have been designed to enable you to easily customize the formatting of the elements that are found in most common tables. If you find the default styles do not provide the level of control you need, you can define new styles. Provided the new style names follow the Word xport s style naming rules, the new styles will be used next time you run the export using the new or amended template. This section provides information on how to do this. Annotations Table headers and footers are positioned around the tables to which they relate (not in Word page headers and footers) and are not exported when you select the option to export charts only. Changing the Microsoft Word xport Orientation to Landscape The default Microsoft Word export template uses Portrait orientation. You can change this to Landscape in an individual Word document, or you can create your own custom template by editing the default template. To create a custom Word template with Landscape orientation: xport an example table to Word, specifying an output file name and folder in the xport File Name field in the Microsoft Word xports dialog box. When the export is complete you will see in the output folder, in addition to the exported Word document, a template file called WordTemplate.dot. Open Word, then open WordTemplate.dot (do not open the.dot file by double-clicking on it as this would create a new document). From the File menu in Word, choose Page Setup, then select Landscape in the Orientation section of the Page Setup dialog and click OK. You may also want to make other changes to the template, for example to resize or reposition the logo. Save and close WordTemplate.dot. You can save this template in any folder (if you export to a folder and IBM SPSS Data Collection Survey Reporter finds an existing WordTemplate.dot in the folder, it does not overwrite it, so your changes are not lost) but you may want to save it to the folder where all your other Word templates are stored, and give it a new name. If you rename the template and/or save it to a folder other than the output folder, you must explicitly select the template when you run the export.

396 382 Chapter 16 Using Survey Reporter, run the export again, selecting the amended Word template in the Apply Word Template field of the xport dialog box. Changing the Headers and Footers Used in the Table of Contents When you export a table from IBM SPSS Data Collection Survey Reporter to a Microsoft Word document, each part of the table is mapped to its own style in Word. A list of the styles is available in The Default Microsoft Word xport Styles. The table of contents in Word documents exported from Survey Reporter is compiled from any text that is formatted in a style based on Word s heading styles (Heading 1, Heading 2, or Heading 3). In the default template, the only style that this applies to is the Annotation LeftHeader style, which is based on the Heading 1 style. This style is used to format all text that appears in the left header of the table. This means that all text in the left header is included in the table of contents. All other header and footer styles are based on the Annotation style,whichinturnisbasedon the Normal style, and do not appear in the table of contents. This example shows you how to display the table description in the Header Center annotation position instead of in the Left Header position, but still use the description in the table of contents. To do this, you need to change the content of the two annotation positions, and change the formatting used in the annotation styles in the Word template. To change the header or footer used in the table of contents: Using Survey Reporter, change the headers and footers so that the text that you want to appear in the table of contents is in the correct position. For example, remove the field {TableDescription \n} from the Header Left position, and add it to the Header Center position. xport an example table to Word, specifying an output file name and folder in the xport File Name field in the Microsoft Word xports dialog box. When the export is complete you will see in the output folder, in addition to the exported Word document, a template file called WordTemplate.dot. Open Word, then open WordTemplate.dot (do not open the.dot file by double-clicking on it as this would create a new document). Open the Modify Style dialog: From the Home tab in Word, expand the available styles under the Styles section. This opens the Styles dialog box. From the Styles list, select the AnnotationCenterHeader style, click the down arrow and then select Modify... In the Style Based On field, change the style from Annotation to Heading 1. This changes the formatting of the style, so you should also reset the font size and any other formatting to what it was before. Then click OK. In the same way, select the AnnotationLeftHeader style and change the style that it is based on from Heading 1 to Annotation.

397 383 Publishing Your Results Save and close WordTemplate.dot. You can save this template in any folder (if you export to a folder and Survey Reporter finds an existing WordTemplate.dot in the folder, it does not overwrite it, so your changes are not lost) but you may want to save it to the folder where all your other Word templates are stored, and give it a new name. If you rename the template and/or save it to a folder other than the output folder, you must explicitly select the template when you run the export. Using Survey Reporter, run the export again, selecting your customized Word template in the Apply Word Template field of the Word xports dialog box. Positioning the Output in a Microsoft Word xport File Using Bookmarks Bookmarks are used in the default Microsoft Word template to position the tables, project and table document descriptions, and table of contents. The following table lists the recognized bookmarks. Bookmark Name xport SurveyTitle ContentsPage Description Indicates where the tables and/or charts are to be inserted. If this bookmark does not exist in the template, they are inserted after the table of contents. Indicates where the project and table document descriptions are to be inserted. If this bookmark does not exist in the template, these items are inserted at the start of the document. Indicates where the table of contents is to be inserted. If this bookmark does not exist in the template and the table of contents option is selected, the table of contents is inserted after the project and table document descriptions. If this bookmark exists in the template when you are not using the table of contents option, you will find that a blank page is created at the bookmark. To insert bookmarks in a template: Open the template in Word. If required, add any standard graphics or text (such as logos, introductory text, and page headers and footers) that you want to appear in the Word documents. Place the cursor on a new line where you want the content to appear. From the Insert menu in Word choose Bookmark. This opens the Bookmark dialog box. nter the Bookmark Name. Click Add. Repeat the steps 3-6 for any other bookmarks that are required. Save the template.

398 384 Chapter 16 Working with Microsoft Word Styles The Microsoft Word export uses a number of paragraph styles to format different types of text. You can change the appearance of the various texts by changing the styles. You can do this in the template or in the Word document itself. Working in the template has the advantage that the styles can be used in multiple documents. In Word, each paragraph style has a name and defines a combination of formatting characteristics, such as font, font size, color, and emphasis, and text alignment, indentation, and spacing. When you apply a specified style to an item, all of the formatting that is stored in that style is automatically applied to the item. By changing the formatting defined for a style, you can quickly change the formatting of all of the items to which the style has been applied. The custom styles used by the Word export fall into four groups: Annotation. Controls the formatting of the headers and footers. Axis. Controls the formatting of the row and column heading texts. Cell. Controls the formatting of the cell contents. Survey. Controls the formatting of the project and table document descriptions shown as a document title, typically on the front page. In the default template the base style in each group of styles is based on thenormal paragraph style. This means you can change, for example, the base font in all of the tables that have been exported using the default template, by simply changing the font in the template s Normal paragraph style. In addition all of the other styles within each group are in turn based on the previous style within the group. This makes it easy to change the formatting of all of the styles in a group. The names of all of the styles in the Axis group start with Axis, the names of the styles in the Cell group start with Cell, and the names of the styles in the Survey group start with Survey. When formatting a text, the export searches the appropriate group of styles for the closest matching style. If there is no suitable style in the style group, the Normal style is used. The table of contents in the Word document is compiled from any text that is formatted in a style based on Word s heading styles (Heading 1, Heading 2, Heading 3). In the default template, the only style that this applies to is the Annotation LeftHeader style, which is based on the Header 1 style. This means that all text in the left header annotation is included in the table of contents. All other annotation styles are based on the Annotation style and do not appear in the table of contents. The easiest way to understand how it works is to create some tables of different types and export them to Word using the default template, and then examine the styles that are applied to the different texts. An easy way to find out which style is applied to a text is to use the Formatting toolbar. When you place your cursor in a text in Word, the style that is applied to the text is shown in the Styles box on the Formatting toolbar. Tip: If the Styles box is not shown on the Formatting toolbar, you can add it using the Customize dialog box. First open the dialog box by choosing Customize from the Tools menu. Then select the Commands tab and drag the Styles category to the toolbar. When the Customize dialog box is

399 385 Publishing Your Results open, you can enlarge the Styles box by dragging the border with your mouse. When you close the dialog box, the Styles box will retain its new size. The following diagram shows the default styles that are applied to a table of Age by Gender that has one item of cell contents (counts) and a mean element in the side axis. Figure Word table with default styles Notice that three different styles are used for the cell contents Cell TopBottom Base Count, Cell TopBottom Category Count, andcell TopBottom and that all three of these styles are in the Cell group: The Cell TopBottom Base Count style is the closest match for the cell contents in the cells formed from the base elements. The TopBottom subgroup is used because there is only one item of cell contents, the Base subgroup is used because the cells are formed from a base element, and the Count subgroup is used because the cell contents are counts. A similar logic governs the choice of the Cell TopBottom Category Count styleforthecell contents in the cells formed from the category elements. The Cell TopBottom style is the closest match for the cells formed from the mean element because there is no Cell TopBottom Mean style in the default template. Ifyouwanttodefine special formatting for the cells formed from the mean element, you would create a new style called Cell TopBottom Mean ifyouwantittoapplytoallcellcontenttypes or Cell TopBottom Mean Count if you want it to apply to counts only. Note that you need to create the new style in a template and export the tables again using that template before the new style will be applied. Similar rules govern the styles that control the formatting of the row and column headings. For more information, see the topic The Default Microsoft Word xport Styles on p Note: Unlike when using a cascading style sheet in HTML, in Word you can apply only one paragraph style to an item.

400 386 Chapter 16 The Default Microsoft Word xport Styles The following table lists the custom styles in the default Microsoft Word template. Type Style Description Annotation Annotation The default style for the headers and footers. Annotation TitleHeader Annotation LeftHeader Annotation CenterHeader Annotation RightHeader Annotation TitleFooter Annotation LeftFooter Annotation CenterFooter Annotation RightFooter The styles for the headers. When the option to create a table of contents is used, by default the table of contents is generated from all of the text that has the Annotation LeftHeader style applied to it, as this style is defined as inheriting from the standard Heading 1 style. The styles for the footers. Axis Axis The default style for table row and column headings. Axis Side The default style for row headings. Axis Side Variable The default style for row headings that are formed from variable names and labels. When there is nesting on the side axis, this style controls the formatting of the outer nest only. Axis Side Sublement The default style for row headings that are formed from nested variable names and labels. Axis Side Sublement Base Axis Side Sublement Category Axis Side lement Axis Side lement Base Axis Side lement Category These styles enable you to apply formatting to the row headings that relate to particular types of nested elements. For example, you may want to show the headings that relate to nested base rows in bold. The default style for row headings that are formed from element names and labels. These styles enable you to apply formatting to the row headings that relate to particular types of elements. For example, you may want to show the headings that relate to base rows in bold. You can add additional styles to define formatting for row headings that relate to other element types. For example, you could add an Axis Side lement Mean style to define special formatting for mean rows. See below for a list of the valid element types.

401 387 Publishing Your Results Type Style Description Axis Top The default style for column headings. Axis Top Variable The default style for column headings that are formed from variable names and labels. When there is nesting on the Top axis, this style controls the formatting of the outer nest only. Axis Top Sublement The default style for column headings that are formed from nested variable names and labels. Axis Top Sublement Base Axis Top Sublement Category Axis Top lement Axis Top lement Base Axis Top lement Category These styles enable you to apply formatting to the column headings that relate to particular types of nested elements. For example, you may want to show the headings that relate to nested base rows in bold. The default style for column headings that are formed from element names and labels. These styles enable you to apply formatting to the column headings that relate to particular types of elements. For example, you may want to show the headings that relate to base columns in bold. You can add additional styles to define formatting for column headings that relate to other element types. For example, you could add an Axis Top lement Mean style to define special formatting for mean columns. See below for a list of the valid element types. Cell Cell The default style for cell contents. Cell Top Cell Top Base Cell Top Base ColPercent Cell Top Base Count Cell Top Category Cell Top Category ColPercent Cell Top Category Count These styles enable you to apply formatting to the first item of cell contents in a table that has more than one type of cell contents (for example, counts and column percentages). You can define formatting based on the element and cell contents types. You can add additional styles to define formatting for other types of elements and cell contents. See below for the valid element and cell contents types.

402 388 Chapter 16 Type Style Description Cell Bottom Cell Bottom Base Cell Bottom Base ColPercent Cell Bottom Base ColPropResults Cell Bottom Base Count Cell Bottom Category Cell Bottom Category ColPercent Cell Bottom Category ColPropResults Cell Bottom Category Count Cell Middle Cell Middle Base Cell Middle Base ColPercent Cell Middle Base Count Cell Middle Category Cell Middle Category ColPercent Cell Middle Category Count Cell TopBottom Cell TopBottom Base Cell TopBottom Base ColPercent Cell TopBottom Base ColPropResults Cell TopBottom Base Count Cell TopBottom Category Cell TopBottom Category ColPercent These styles enable you to apply formatting to the last item of cell contents in a table that has more than one type of cell contents (for example, counts and column percentages). You can define formatting based on the element and cell contents types. You can add additional styles to define formatting for other types of elements and cell contents. See below for the valid element and cell contents types. These styles enable you to apply formatting to the middle items of cell contents in a table that has three or more types of cell contents (for example, counts, and column and total percentages). You can define formatting based on the element and cell contents types. You can add additional styles to define specific formatting for other types of elements and cell contents. See below for the valid element and cell contents types. These styles enable you to apply formatting to the items of cell contents in a table that has only one type of cell contents (for example, counts only). You can define formatting based on the element and cell contents types. You can add additional styles Cell TopBottom Category ColPropResults to define specific formatting for Cell TopBottom Category Count other types of elements and cell contents. See below for the valid element and cell contents types. Survey Survey The default style for the document title. Survey Description Survey Name The style for the table document description. The style for the data set description.

403 389 Publishing Your Results The following table lists the valid element and cell contents types that you can use in the styles. Valid lement Types Category Mean StdDev Stdrr SampleVar Total SubTotal Text Minimum Maximum Net Combine xpression Base UnweightedBase Valid Cell Contents Types Count UnweightedCount Sum Minimum Maximum Mean Range Mode Median Percentile StdDev Stdrr Variance Residuals xpectedvalues Indices ColPropResults ColPercent RowPercent TotalPercent CumColPercent CumRowPercent Creating and Modifying Microsoft Word Paragraph Styles You can modify styles in your exported Microsoft Word document, or in the template (.dot) file, using Word s Style dialog box. To modify a paragraph style: Open the Modify Style dialog: From the Home tab in Word, expand the available styles under the Styles section. This opens the Styles dialog box. From the Styles list, select the paragraph style that you want to modify, click the down arrow, andthenselectmodify... If you want to save the changes that you make to the template, select Add to template. To change the font, click Format and select Font. Select the required font and font size. To change the paragraph formatting, click Format and select Paragraph. Select the required options. Click OK. To create a new paragraph style: Open the New Style dialog box: From the Home tab in Word, expand the available styles under the Styles section. This opens the Styles dialog box. Click the New Style icon.

404 390 Chapter 16 nter the new style Name, using the naming rules explained in The Default Microsoft Word xport Styles. Set the Style Type to Paragraph. If you want to base the formatting on another style, select the required style in the Based On drop-down list. Select the appropriate formatting options you require. If you want to save the changes that you make to the template, select Add to template. Click OK. xporting Data You can export selected data from the currently open survey data file to a number of different file formats such as IBM SPSS Statistics SAV files, delimited text files for use in Microsoft xcel, IBM SPSS Quantum DAT files, or SAS system files. The export creates a new file in the location that you specify. New variables and variable edits are also exported. Notes: xporting data is only possible from the desktop version of IBM SPSS Data Collection Survey Reporter. You cannot export data from the version of Survey Reporter that is installed from a server. xporting new or edited variables that contain an up-lev expression (for example, MalesInHouseHold "Males live in the household" Boolean expression("sum(person.(gender = {male})) > 0") or an expression that references the level ID (for example a derived grid such as LikesOurBrand "Respondent likes our brand" Boolean expression("levelid = {OurBrand} And Rating * {VGood, xcellent}") is not supported. You can choose to export data for all the variables in the survey data file, or you can select variables to export using the Variables pane, or select particular types of variables to export. You can also apply a filter to restrict the data to export, by setting up a global, table, or interview filter in Survey Reporter before you export the data. To export data If required, set up any filtering that you want to use. You can apply a global, table, or interview filter, or any combination of these. For more information, see the topic Filtering Your Results in Chapter 6 on p. 92.

405 391 Publishing Your Results If you do not want to export all variables, use Shift+click or Ctrl+click to select the variables you do want to export in the Variables pane. Tip: Ifyoufrequentlywanttoexportthesamevariables,youmaywanttoaddthemtoafolderso that they are in the same place and you can select them using Shift+click. For more information, see the topic Organizing Variables in Chapter 3 on p. 46. From the menu, choose File > xport > Data The xport Data dialog box appears. In the General tab: If the survey data file you are exporting from includes more than one language, select the language to export from the drop-down list. Select the output file format you want to use. Depending on the file format you select, additional options may be available. For more information, see the topic xport Data Dialog Box: General Tab on p nter a name for the output file. If you do not enter a file path, the file will be saved in the same folder as the survey data file. To save the file elsewhere, choose the Browse button and select the location for the exported file. In the Variables tab: Ifyouwanttoexportallvariablesinthesurveydatafile, choose the All variables option. If you want to export the variables you have selected in the Variables pane, choose Variables currently selected in the variable list. To see a list of the selected variables, check the View selection box. If you want to export all variables of a particular type, for example, all categorical variables, choose the Specific types of variables option and check the relevant boxes. Choose whether to include system variables. You can choose common system variables or all system variables. Choose which variables should be exported for the axis variable. In the Filters tab: Choose the filter or filters to apply to the data before it is exported. Only the data that passes the filter(s) will be exported. When you have finished entering your export options, choose OK to export the data. xport Data Dialog Box: General Tab Use the General tab of the xport Data dialog box to enter details of the output file that you want to export to, and to select a language for the export.

406 392 Chapter 16 Fields on the General Tab Variable description language. Choose the language in which you want variable and category descriptions to be exported. The drop-down list shows all of the languages that are available in the current survey data file. xport format. Choose the format in which to save the exported data. Available formats are: IBM SPSS Statistics File (SAV) Delimited Text File (Microsoft xcel) IBM SPSS Data Collection Data File (ddf and compressed dzf formats) IBM SPSS Quantum Data File (DAT) SAS System File Triple-S File (Fixed or CSV) IBM SPSS Data Collection XML Data File Metadata Only Advanced File name. nter a name and file path for the output file. The remaining sections of this dialog box are specific to the export format you have selected: SPSS Statistics File (SAV). IfyouareexportingdatatoSPSSStatistics.SAV format for use with versions of SPSS Statistics prior to version 12, check the Use SPSS Statistics SAV short file names box to export variable names with a maximum length of eight characters. xport Factors. When selected, case data for single-response categorical variables that have factor values, are exported as factor values (or missing values for non-factor elements). The case data are not exported as categorical values. xport Variables in Different Levels into Different Files. When selected, variables are exported, in one or multiple files, and grouped together in the same hierarchical level. The export process creates a new file for each unbounded level that has variables selected from it. A separate record is created in the output file for each record at the level being exported. SAS System File. If you are exporting data to SAS system file format, ensure that the xport Factors box is checked if you want to export factors set for the categories in IBM SPSS Data Collection Survey Reporter as category values in the SAS file (this is the default for SAS). Deselect the box if you want to export the native values (sequential values starting from 1). Quantum Data File (DAT). IfyouareexportingdataintoaQuantumDATfile format, a set of prompts to do with card column options is displayed. Do the following: In the Width of serial number field, type the number of columns to reserve for the respondent serial number. The default is five columns. In the Width of card number field, type the number of columns to reserve for the card number. The default is two columns.

407 393 Publishing Your Results In the Max card length field, type the maximum number of columns to write per card. The default is 80. Leave this field blank for an infinite card length. In the Full name of serial variable field, enter the name of the variable that contains the respondent serial numbers. In survey data files created by Data Collection products this variable is called Respondent.Serial, but in files from other sources it may have another name, for example, Serial. Metadata Only. When selected, this option only saves the metadata document as loaded by Survey Reporter (the Variable tab and filtering options are not available). Advanced. If you select the Advanced option, choose the dit button to display the Data Link Properties dialog box, where you can specify the connection properties for your required export format. xport Data Dialog Box: Variables Tab Use the Variables tab of the xport Data dialog box to select the variables for which you want to export data. Fields on the Variables Tab All variables. xports all variables in the survey data set that is open in IBM SPSS Data CollectionSurveyReporter. Variables currently selected in the variable list. If you do not want to export all variables, select those that you do want to export using the Variables pane, then check this box. View selection. Check this box to see the variables selected in the Variables pane. If you want to change your selection, choose cancel to return to the main Survey Reporter window, and use Shift+click or Ctrl+click to select the required variables. Specific types of variables. Use this option to export only variables of a particular type or types. Choose any of: Text Categorical Numeric - long Numeric - float Boolean Date Categorical with other specify

408 394 Chapter 16 Include system variables in export. If you want to export system variables, check this box, and choose from: Common system variables. System variables contain general information about the questionnaire as a whole rather than data related to an individual question and, as such, they may be of little use for analysis purposes. However, rather than forcing you to choose between exporting all or no system variables, xport Data offers a third option of exporting only the more commonly used system variables. All system variables. xport special data elements (e.g., Base, Net). When selected, special data elements are also exported. Refer to the Special lements topic in the Data Collection Developer Library for more information regarding special elements. Variable edits. These options allow you to select which variables should be exported for the axis variable. xport edited definition. When selected, only the edited, derived axis variable definition name is exported. xport original definition. When selected, only the original variable definition name is exported. xport original and edited definitions. When selected, both the original variable definition and the edited, derived axis variable definition names are exported. xport Data Dialog Box: Filter Tab Fields on the Filter Tab Use the Filter tab of the xport Data dialog box to apply filters to the data. Only cases that pass the filter are exported. Apply global filter. Applies a filter that you have set up using the Global Filter dialog box. For more information, see the topic Global Filters in Chapter 6 on p Apply interview filter. Applies a filter that you have set up using the Interview Filters dialog box. For more information, see the topic Interview Filters in Chapter 6 on p Apply filter from current table. Applies the filter from the selected table. For more information, see the topic Table Filters in Chapter 6 on p. 99. Distributing Data and Results You can supply your results to other departments or organizations in a variety of formats, for example, by exporting results to HTML or Microsoft Office applications (see xporting Results), or by exporting selected variables from IBM SPSS Data Collection Survey Reporter to a number of different file formats (see xporting Data).

409 395 Publishing Your Results Another method is to supply the source files (including the survey data files and the table document files) to other departments or customers who also use Survey Reporter. This enables the recipients to see the original data as well as the results, and to carry out their own additional analyses if required. This section provides information for anyone who needs to distribute data or results from Survey Reporter for use in another department or organization. Transferring Table Documents Between IBM SPSS Data Collection Survey Reporter and Other Applications You can open table document files created in IBM SPSS Data Collection Base Professional or IBM SPSS Data Collection Survey Tabulation using IBM SPSS Data Collection Survey Reporter. You can also use table document files created in Survey Reporter with Base Professional or Survey Tabulation. Profile tables and difference attribute tables can be created in Survey Reporter and Base Professional but not in Survey Tabulation. If you open a table document containing such tables using Survey Tabulation, you can see the table definitions and you can populate the tables and view the results, but you cannot edit the tables. Table folders created in IBM SPSS Data Collection Survey Reporter or Base Professional are not displayed in Survey Tabulation, but any tables in the folders are displayed as normal. For information on how to open table documents from other applications in Survey Reporter, see Opening Table Documents from Other Applications. Supplying Source Files and Results to Customers If you want to send the original survey data files and the resulting table document (.mtd) files to another department or a customer who also has IBM SPSS Data Collection Survey Reporter, this procedure ensures that the subsidiary files are also supplied. To save the table documents In Survey Reporter, openasurveydatafile and create tables and charts as usual. When saving your work: if you save all your tables in a single table document (.mtd) file, save the file in the same folder as the survey data files. if you save your tables in multiple table documents, save each table document file in a separate sub-folder beneath the survey data files.

410 396 Chapter 16 To save the variable preview files If you make use of the Variable Preview in Survey Reporter, you should also supply the variable preview cache files along with the data and table document files, so that the recipient of the data can access the previews without having to regenerate them. The process for supplying these filesisasfollows: In Windows xplorer, create a sub-folder beneath the folder containing the table document file, and give it the name Variable Preview Cache (the folder must have exactly this name). In Survey Reporter, open the table document file and choose File > Properties In the Location field on the Advanced tab, you will see the name and path of the temporary folder where the variable preview files are located, for example, C:\Documents and Settings\username\Local Settings\Temp\Variable Preview Cache\tmp19. Select and copy this file path. In Windows xplorer, paste the file path into the Address field to go directly to the folder. Copy all the files and sub-folders in the temporary folder. Do not copy the temporary folder itself. Paste all the files and sub-folders into the Variable Preview Cache folder that you created beneath the folder containing the table document file. Repeat these steps for each table document file. When you supply the files to another employee or to a customer, include the entire folder containing the data source files and all the sub-folders, and ensure that you retain the sub-folder structure when packaging the files. Changing the Logo Displayed in the Results Pane By default, the IBM Corp. logo is displayed on all tables in the Results pane. You can turn this off, or you can replace it with your own logo in.png file format. To remove the logo From the menu, choose Tools > Options The Options dialog box appears. On the Display tab, choose the Results Display Options button. In the Results Display Options dialog box, choose the Advanced button.

411 397 Publishing Your Results Uncheck the Logo check box, and choose OK in all the open dialog boxes. The logo is no longer displayed in the Results pane. To change the logo to your own logo Save your company logo in.png file format, and add it to the folder that contains the survey data file. From the menu, choose Tools > Options On the File Locations tab, choose the Browse button next to the Table logo field and select your logo file. Choose OK. Ifyouhavepreviouslyturnedoffthelogodisplay,checktheLogocheckboxintheResultDisplay Options dialog box to turn it on again. The new logo is now displayed in the Results pane.

412 Chapter 17 Converting IBM SPSS Quanvert Table Specification (.qsf) files to Data Collection Table Document (.mtd) files You can use the IBM SPSS Quanvert to Data Collection Table Document Files Conversion wizard to convert Quanvert Table Specification (.qsf) files to Data Collection Table Document (.mtd) files. When you open a Quanvert Table Specification (.qsf) file in IBM SPSS Data Collection Survey Reporter, the wizard automatically displays and walks you through the conversion process. When the wizard opens: Click Next on the welcome screen. On the Ready to Convert screen, review the summary information, specify the appropriate Quanvert project on which the.qsf is based, and click Next to begin the conversion process. A new Data Collection Table Document (.mtd) file will be created in the same directory as the source Quanvert Table Specification (.qsf) file. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

413 Chapter 18 Customizing IBM SPSS Data Collection Survey Reporter IBM SPSS Data Collection Survey Reporter has many features that you can use to customize the application according to your requirements. This section includes information on the options available. Customizing Table Document Templates Whenyouopenasurveydatafile, a new table document is automatically created. When you create tables, they are added to this table document. The settings that apply to the tables for properties such as headers, footers, cell contents, and so on, are taken from the default IBM SPSS Data Collection Survey Reporter settings. For example, by default, all tables display Counts and Column percentages. You can change these settings for one or more tables using the Table Properties dialog box. You can change the settings for all new tables in the current table document, or for tables in all new table documents. You can also save your settings as defaults so that all new tables that you create use your own settings instead of the system defaults. This creates table document template. For example, you may find that you almost always want to include Counts in your tables but not Column percentages, and that you want all your tables to display filter details in the right footer rather than the left header. You can do this by changing these properties in the Table Properties dialog box and saving the settings as defaults. This creates a table document template with the new settings. Whenever you open a survey data file, the new table document that is created will apply the settings from the template to all the tables that you create. If you subsequently need to include Column percentages (or any other cell contents) in a particular table, you can use the Table Properties dialog box to change the cell contents, and apply the changes to just that table. A table document template is similar to an ordinary table document (.mtd) file, except that in most cases it does not contain any tables or references to specific survey data files. However, you can also create a template by setting up a table document with the defaults that you require, removing the information about the survey data, saving the file in the templates folder, and specifying the new file as a template in Survey Reporter. In this case, the file can contain tables as well as table properties. When you open a survey data file, Survey Reporter uses the defaults in the template.mtd file, if there is one, for all the tables in the new table document. If no template exists, the default settings supplied with Survey Reporter are used. You can override these defaults for selected tables or for all tables that you create. When you save a table document, the settings you have applied to specific tables are saved, rather than those in the template. When you subsequently Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

414 400 Chapter 18 reopen a table document that you have saved, the settings in that table document apply, not the settings in the template. Properties affected by template files You can set the following table properties as defaults in a template file so that they are applied to new table documents. Cell Contents Display Options Statistics Headers and Footers Chart Types Properties not affected by template files You cannot set the following table properties as defaults in a template. This is because they refer to specific variables, which may not be present in another survey data file. Weights Hiding rows, columns or cells Levels Sorting rows or columns If you are using a template that contains tables as well as table property settings, however, you can set these properties for individual tables. Creating a Table Document Template When you change properties in the Table Properties dialog box, you have the option to apply the changestoallnewtablesbysavingtheminatabledocumenttemplate. To create a template using the Table Properties dialog box Use the Table Properties dialog box to change the settings that you want to use as the defaults. In the Table Properties dialog box, choose Set as Default. In the Default Cell Contents dialog box, check the box to update the document template, and choose OK. A new template file is automatically created if one does not already exist, and the changes from theselectedtabaresavedtothetemplate. When you subsequently save any changes to the template, the template file is updated.

415 401 Customizing IBM SPSS Data Collection Survey Reporter The template file that IBM SPSS Data Collection Survey Reporter creates is called template.mtd and is saved in a sub-folder of the Documents and settings folder under your user name, for example, C:\Documents and Settings\<your Windows user name>\application Data\IBM\SPSS\DataCollection\6\Survey Reporter\template.mtd. Note: The Set as Default option applies the changes only for the currently selected tab in the Table Properties dialog box. To apply the changes for more than one tab to the template, choose the Set as Default button in each tab individually, and follow the same steps. Creating a Template From a Table Document You can create a template by setting up a table document with the defaults that you require, removing the survey data file information, and saving the file in the templates folder. You can then select this file as the template in IBM SPSS Data Collection Survey Reporter. This is an advanced feature that is useful for organizations who want to save not just default settings for table properties but also default tables. For example, you may want to set up a standard set of tables that you want to use with different survey data files, perhaps to analyze sets of responses from different countries or successive batches of results from a survey that is run on a regular basis. Note that if you create templates containing tables, the tables will be valid only when used with survey data files that contain the same or similar variables. For example, if you create a template that includes tables defined using a particular numeric variable, using the template with another survey that uses a categorical variable to store the same data will result in invalid tables. To create a template from an existing table document Create a new table document file. Set up the tables you want to include in the template. Use the Table Properties dialog box to change the table properties to your requirements, either for individual tables or for all tables. From the menu, choose File > Advanced In the Advanced dialog box, check the Include table and profile results when saving box. Choose the Copy without Dataset button. This removes the details of the metadata and case data files when the table document file is saved. nter a file name and location for the new table document in the Save As dialog box, then choose OK. Templates can have any name, but must have the file extension.mtd. You can save the file in the default template folder, or in another suitable folder. For example, you may want to create a template for use by everyone in the department. In this case, you probably want to set your template file to be read-only and save it on a network drive. The default template folder is a sub-folder of the Documents and settings folder under your user name, for example, C:\Documents and Settings\<your Windows user name>\application Data\IBM\SPSS\DataCollection\6\Survey Reporter. If you have previously used the Save as

416 402 Chapter 18 Default option in the Table Properties dialog box, a default template called template.mtd will already exist in this folder. Once you have set up your template and saved it in a suitable location, you need to change the File Locations tab of the Options dialog box to point to the new template. From the menu, choose Tools > Options In the File Locations tab, choose the Browse button next to the Template file field, and select the table document file that you created in the previous steps. Then choose OK. When you subsequently open any survey data file, the table document that is created automatically picks up the default settings from the new template file. You can make further changes to the template file by using the Table Properties dialog box, choosing Set as Default, and checking the option to update the template file as usual. Alternatively, you may wish to prevent this by setting your template file properties to read-only in Windows xplorer so that you do not accidentally overwrite the template settings. Removing a Template Once you have created a template, either by using the Table Properties dialog box or by adding your own template file to the templates folder, all new tables that you create in the current table document and in new table documents take their default settings from the template. You can, of course, change the settings for individual tables or for selected tables using the Table Properties dialog box. You can also change settings for all tables in the current document without applying the changes to the template. If you want to revert to the IBM SPSS Data Collection Survey Reporter default settings, you can do so by removing the template file in Survey Reporter. To remove a template file From the menu, choose Tools > Options In the File Locations tab, highlight the full path and file name of the template in the Template file field and delete it. Choose OK to close the Options dialog box and save the change. When you subsequently open a survey data file, the new table document that is created uses the Survey Reporter default settings. Customizing the Format of Your Results The formatting in the Results tab (and in files exported using the HTML xport option) is controlled by a style sheet. A number of style sheets are supplied with IBM SPSS Data Collection Survey Reporter. You can change the format of the Results tab by selecting a different style sheet from the drop-down list in the toolbar, or by choosing from the list in the Display tab

417 403 Customizing IBM SPSS Data Collection Survey Reporter of the Options dialog box. For example, here is a table formatted using the Black and White style sheet: Figure 18-1 Table formatted using Black and White.css Here is the same table formatted using the Color Code style sheet: Figure 18-2 Table formatted using Color Code.css The style sheet is actually a cascading style sheet (.css) file, which can be edited in a text or HTML editor, and which determines how each part of the output is formatted. In the first example above, the column percentage cell items are formatted in italics. This is controlled by the following sectionintheblack and White.css file: TD.CellItemColPercent { FONT-STYL: italic; } TD.CellItemColPercent identifies the column percentages cell item, and the information in curly braces {} defines the formatting for that item, in this case by setting the FONT-STYL property to italic. In the Color Code style sheet column percentages are displayed in a shade of red, instead of in italics. Here is the equivalent section of the Color Code.css style sheet: TD.CellItemColPercent { COLOR: #7C13F; } In this case, the Color property is set to #7C13F, which is simply a numerical value that corresponds to a specific shade of red. Youcanmodifytheexistingstylesheetsorcreateyourown.Youcanalsomodifythestylesheets used by the HTML xport option.

418 404 Chapter 18 diting Style Sheets You can edit cascading style sheet (.css) files using any standard text editor or HTML-authoring tool. You can edit the supplied style sheetsorcreateyourown. Ifyoucreateyourownstyle sheets it is usually easiest to copy an existing style sheet that is close to the style that you want, and change the settings as required. By default, style sheets used to format tables in the Results tab are located in C:\Documents and Settings\All Users\Application Data\IBM\SPSS\Survey Reporter\ \Styles. Youcansave your own style sheets in this location or you can save them in another location and change IBM SPSS Data Collection Survey Reporter to point to the new location using the Style Templates field in the File Locations tab of the Options dialog box. To edit a style sheet Note: Do not edit style sheets in the style sheet folders, delete existing style sheets, or add new ones while Survey Reporter is running. Close Survey Reporter. In Windows xplorer: if you are editing an existing style sheet, make a backup of the.css file first. if you are creating a new style sheet, make a copy of the.css file that you want to base your new style sheet on and give it a new name. This can be any name that is valid in Windows xplorer; however, the name will appear in the drop-down list in the Results tab, so it is a good idea to use a fairly short name that briefly describes the content. Open the.css file in a text or HTML editor and edit it as required. Save and close the file. Open Survey Reporter, select the Results tab, and select the new style sheet from the drop-down list in the toolbar. You can also export tables using the edited style sheet by selecting it from the Table presentation drop-down list in the HTML xport dialog box. For more information, see the topic HTML xports in Chapter 16 on p diting Style Sheets: xample Suppose you want to amend the Black and White style sheet to show the Left Header annotation in color, a larger size, and bold, and to format the cell contents that show the sum of a numeric variable in the same color and italics. In addition, you want to highlight the horizontal side axis text by changing the font color, and also the background color of the cell and the side indent cell. You could do this by making the following changes to the Black and White.css file:... TD.CellItemCount, TD.CellItemUnweightedCounts {

419 405 Customizing IBM SPSS Data Collection Survey Reporter } TD.CellItemSum { FONT-STYL: italic; COLOR: #800080; } TD.CellItemMin,... { }... TD.AxisLabelHorizontalSide { FONT-WIGHT: bold; FONT-SIZ: 11pt; FONT-STYL: normal; FONT-FAMILY: Arial, sans-serif; TXT-ALIGN: left; COLOR: white; BACKGROUND: gray; } TD.AxisLabelIndentSide { BACKGROUND: gray; }... TD.LeftHeader { WIDTH: 30%; TXT-ALIGN: left; FONT-WIGHT: bold; FONT-SIZ: 10pt; COLOR: #800080; }...

420 406 Chapter 18 Here is a table of Age by Gender showing the sum of the visits variable, formatted using the amended version of the Black and White style sheet: Figure 18-3 HTML export using amended style sheet Style Sheet Settings The style sheet contains a number of styles that define the format of the different items in the tables, annotations, and table of contents. You can change the appearance of the various items by changing the styles. The styles fall into a number of groups according to the items whose formatting they control. The following diagram shows the main style groups and indicates which area of the table they format.

421 407 Customizing IBM SPSS Data Collection Survey Reporter Figure 18-4 HTML export styles Data Cell Items These styles control the formatting of the table cells that contain figures (cell contents). Type Style Description Cell TD.Cell The default style for the table cells that contain figures (cell contents). Cell position Cell element type TD.CellTop TD.CellBottom TD.CellMiddle TD.CellTopBottom TD.CelllementCategory TD.CelllementMean TD.CelllementStdDev TD.CelllementStdrr TD.CelllementSampleVar TD.CelllementTotal TD.CelllementSubTotal TD.CelllementText TD.CelllementNetDiffs TD.CelllementPairedPrefs TD.CelllementOtherDerived TD.CelllementMinimum TD.CelllementMaximum TD.CelllementNet TD.CelllementCombine TD.Celllementxpression TD.CelllementTableStatistic TD.CelllementNumeric These styles enable multiple cell items to be enclosed within a single border. These styles apply individual formatting to the cells that relate to particular types of category and other items appearing in rows or columns, for example, to show the cells formed from the base rows and columns in bold.

422 408 Chapter 18 Type Style Description Cell items TD.CelllementDerived TD.CelllementSum TD.CelllementMedian TD.CelllementPercentile TD.CelllementMode TD.CelllementBase TD.CelllementUnweightedBase TD.CellItemCount TD.CellItemUnweightedCounts TD.CellItemSum TD.CellItemMinimum TD.CellItemMaximum TD.CellItemMean TD.CellItemRange TD.CellItemMode TD.CellItemMedian TD.CellItemPercentile TD.CellItemStdDev TD.CellItemStdrr TD.CellItemVariance TD.CellItemResiduals TD.CellItemAdjustedResiduals TD.CellItemxpectedValues TD.CellItemValidN TD.CellItemIndices TD.CellItemColPropResults TD.CellItemColBase TD.CellItemRowBase TD.CellItemColPercent TD.CellItemRowPercent TD.CellItemTotalPercent TD.CellItemCumColPercent TD.CellItemCumRowPercent TD.CellItemProfileResult These styles specify formatting for different types of cell contents, for example, to format column percentages differently from counts. Table Axis Cell Items These styles control the formatting of the cells that form the row and column headings. Type Style Description Axis TD.Axis The default style for the table cells that contain the row and column headings.

423 409 Customizing IBM SPSS Data Collection Survey Reporter Type Style Description Cell type lement type TD.AxisLabelTop TD.AxisLabelSide TD.AxisLabelHorizontalSide TD.AxisLabelIndentSide TD.AxislementTop TD.AxislementSide TD.AxisSublementLevelnTop TD.AxisSublementLevelnSide TD.AxisColumnHeading TD.AxislementSortedOn TD.AxislementCategory TD.AxislementMean TD.AxislementStdDev TD.AxislementStdrr TD.AxislementSampleVar TD.AxislementTotal TD.AxislementSubTotal TD.AxislementText TD.AxislementNetDiffs TD.AxislementPairedPrefs TD.AxislementOtherDerived TD.AxislementMinimum TD.AxislementMaximum TD.AxislementNet TD.AxislementCombine TD.Axislementxpression TD.AxislementTableStatistic TD.AxislementNumeric TD.AxislementDerived TD.AxislementSum TD.AxislementMedian TD.AxislementPercentile TD.AxislementMode TD.AxislementBase TD.AxislementUnweightedBase These styles apply formatting to the various items that make up the column and row headings. These styles apply individual formatting to the row and column headings that relate to particular types of category or other items appearing in rows or columns, for example, to show the headers that relate to base rows and columns in bold. Table of Contents These styles control the formatting of the table of contents. Type Style Description Table of contents cell TD.TableOfContents Controls the formatting of the table of contents cells. Table of contents title cells TD.TableOfContentsTitle Controls the formatting of the table of contents column headers.

424 410 Chapter 18 Annotations These styles control the formatting of the annotations (headers and footers). Type Style Description Annotation TD.Annotation The default style for the table annotations. Annotation type TD.TitleHeader TD.LeftHeader TD.CenterHeader TD.RightHeader TD.TitleFooter TD.LeftFooter TD.CenterFooter TD.RightFooter These styles define individual formatting for the annotations in each annotation position. Tip: The default annotation styles define the percentage of the total width that is to be used for the left, center, and right header and left, center, and right footer annotations. If you do not use one or two of the header or footer annotation positions, you may want to increase the percentage allocated to the positions you do use and reduce the percentage allocated to the position or positions you don t use. This means that more text will be displayed on each line and reduce the line wrapping. For example, if you never use center headers, you could reduce the width allocated to the TD.CenterHeader style to 0% and increase the percentage width allocation in the TD.LeftHeader and TD.LeftHeader styles. General These styles control the formatting of other items. Type Style Description Top link A.TopLink Controls the formatting of the link that returns the user to the top of the HTML document. Used in the Single Document layout style only. Survey Name and Description Picture / Chart H1.SurveyName H1.SurveyDescription IMG.TableImage IMG.TableLogo Controls the formatting of the survey title and description. nablesimagestohaveaspecified background color. Vertical Spacer.VerticalSpacer Controls the vertical gap between the row headers and the cells that form the body of the table. Horizontal Spacer.HorizontalSpacer Controls the horizontal gap between the column headers and the cells that form the body of the table. For detailed information on working with styles, refer to standard CSS documentation. At the time of writing, information about CSS technology is available at MSDN: Cascading Style Sheets (CSS) ( ( ).

425 411 Customizing IBM SPSS Data Collection Survey Reporter For a list of colors, see HTML Color Names ( at Changing File Properties You can change a number of default settings in the current table document (.mtd) file using the File Properties dialog box. Changes that you make in this dialog box apply to all tables in the current.mtd file. To display this dialog box, choose File > Properties from the menu. File Properties: General Tab The General tab of the File Properties dialog displays information about the current table document (.mtd) file. If required, you can change the table description. Fields on the General Tab File name. Displays the name of the table document file. File location. Displays the full file path. Description. nter a description for the table document. File Properties: Data Tab The Data tab of the File Properties dialog displays information about the survey data associated with the table document (.mtd) file. You can change the survey data file used by the table document, or remove the survey data file details so that the table document is not associated with any survey data file, using the Advanced dialog box. Fields on the Data Tab Data Details. Displays information about the survey data file. Metadata location. The name and location of the metadata file. Metadata type. Displaysthetypeoffile that contains the metadata, for example, IBM SPSS Data Collection Metadata Document or IBM SPSS Statistics SAV file. Metadata version. Displays the version of the data being used. Case data location. The name and location of the case data file.

426 412 Chapter 18 Case data type. Displaysthetypeoffile that contains the case data, for example, Data Collection XML Data file or SPSS Statistics SAV file. Project. Data description. Data notes. File Properties: Advanced Tab Use the options in the Advanced tab to change additional details for the current table document. Fields on the Advanced Tab Variable Preview Cache location. When you generate a preview for a variable, a number of files are created to contain the preview information, so that it does not need to be regenerated the next time you look at the variable. This field displays the location of the files. If you are supplying a table document to another person or company and you want them to be able to see variable previews that you have generated, you need to supply these files along with the table document. Data view. Displays the view of the data (hierarchical or flat)thatisinuse.inmostcasesitis better to use the hierarchical view, as this provides additional functionality. For more information, see the topic The Hierarchical View and theflatviewinchapter11onp.264. Variable description language. Choose the language in which you want variable and category descriptions to be displayed in the Variables pane and in the tables that you create. The drop-down list shows all of the languages that are available in the current survey data file. Variable description context. Choose the context for which you want variable and category descriptions to be displayed. By default, IBM SPSS Data Collection Survey Reporter displays analysis text, but you might prefer to display text from another context such as the question context, which shows the text that respondents of the survey were given. The drop-down list shows all of the contexts that are available in the current survey data file. Generate detailed statistical output. Select this option if you want to see diagnostics information on how statistical test results were calculated, including p values, the type of formula used, and the degrees of freedom for the table. For more information, see the topic Displaying Detailed Statistical Output in Chapter 9 on p Delete log files after table generation. By default, log files are deleted once a table has been generated, to save disk space. If you need to keep the log files, for example, because you have been asked to provide them to assist with a support request, deselect this box. Log files are generated in a sub-folder of the Documents and Settings folderunderyourusername,forexample, C:\Documents and Settings\username\Local Settings\Temp. Keep profile data when saving. If you have created any profile tables, you can choose whether to save or discard the data in these tables when you save the table document. Because profile data can increase the table document size substantially but is quick to generate, you may prefer to discard the profile data when you save your table documents, and regenerate the profile tables

427 413 Customizing IBM SPSS Data Collection Survey Reporter again as you need them. Note that only the profile data is discarded; the structure and properties of the profile tables are saved. Include special data elements (e.g., Base, Net) in profile results. When selected, special data elements (such as Net and Base elements) are included in the profile table results. Changing IBM SPSS Data Collection Survey Reporter Options You can change a number of default settings in IBM SPSS Data Collection Survey Reporter using the Options dialog box. Changes that you make in this dialog box apply throughout the application. To display the Options dialog, choose Tools > Options from the menu. Options: General Tab Use the General tab of the Options dialog box to set options that control automatic generation of table descriptions and results. Fields on the General Tab Auto-generate the table description. Controls how IBM SPSS Data Collection Survey Reporter generates the description for new tables. The table description is displayed in the Tables pane andinthetable description text box in the Design tab. Deselect this check box if you do not want Survey Reporter to auto-generate the description, for example, because you want to enter your own description. When you check this box, the table description is automatically generated using one of the following options: Use the table syntax. Select this option if you want the description to be generated from the table definition syntax. This combines the definitions for the side and top of the table. Use the table syntax (label based). Select this option if you want the description to be generated from the table definition syntax, but with the variable names replaced by their descriptions. Use the side axis syntax. Select this option if you want the description to be generated from the definition of the side of the table (shown before the * in the Table Syntax tab). Use the side axis syntax (label based). Select this option if you want the description to be generated from the definition of the side of the table, but with the variable names replaced by their descriptions. When you select any of the auto-generate options, any descriptions you have entered manually are removed from existing tables and replaced with the auto-generated text. When one of the auto-generate options is in use, Survey Reporter automatically regenerates the description whenever you change the structure of the table.

428 414 Chapter 18 Auto-generate counts and percentages in the variable editor. Controls whether Survey Reporter displays counts and percentages for each category in the variable when you open the dit Variable dialog box. If youcheckthisbox, thevaluesaredisplayedautomatically. Ifyou deselectit, youcan still see counts and percentages on demand by choosing the Update Counts button on the toolbar. Options: Display Tab Use the options in the Display tab to control the appearance of the Results tab and to set other options that affect the display in IBM SPSS Data Collection Survey Reporter. Fields on the Display Tab Always generate new and changed tables before viewing. Select this option if you want Survey Reporter to generate results automatically when you select the Results tab. If you deselect this option, results are not displayed until you choose one of the Generate options on the Tables menu or toolbar, or press F5 or Ctrl+F5. Results Display Options. Choose this button to open the Results Display Options Dialog Box, where you can specify how you want your results to look in the Results tab. Shorten long variable names. If your variable names use namespaces, you may want to display the variables in Survey Reporter without using the full namespace, to improve the table display. For example, if your variables have names such as CompanyName.DivisionName.SurveyName.VariableName, youmayonlywantthevariablename part to be displayed in the tables you create. To restrict the length of the variables, select a number of levels from the drop-down list. For survey data containing grid variables, enter a value of at least 2 to ensure that the full grid name is displayed. Results Display Options Dialog Box Use the options in the Results Display Options dialog box to control the appearance of the Results tab. Note: To see your changes in the Results tab, you need to regenerate the results. To display this dialog box, choose Tools > Options from the menu and choose the Results Display Options button in the Display tab. Fields on the Results Display Options dialog box Include. Choose whether to create tables only, charts only, or both tables and charts, and whether to display the chart or the table first. For details of the way in which you can display data in charts, see Displaying Results in Charts. Default chart type. If you have chosen to display charts, select a chart type from the drop-down list.

429 415 Customizing IBM SPSS Data Collection Survey Reporter Presentation. Select the style sheet you want to use to format the results. You can choose from any of the supplied style sheets, or create your own custom style sheet. The style sheets supplied with IBM SPSS Data Collection Survey Reporter are: Black and White Bubble Gum Color Code Compact Grayscale Lilac IBM SPSS Data Collection Survey Tabulation Look SPSS Note: The style sheets listed here are contained in the folder specified in the Style templates field on the File Locations tab. To add your own style sheet to the list, place the style sheet in the same location. For more information, see the topic Customizing the Format of Your Results on p Apply to HTML xport. Choose this button to copy all the settings in this dialog box to the HTML exports dialog box. You can then use the HTML xport options to change individual export options if required. Advanced HML xport Properties Choose the Advanced button to view or edit the Advanced HTML xport Properties dialog box. Display Properties: Variable. Choose whether to use variable names or the more friendly descriptions for the variable texts in the tables. Category. Choose whether to use category names or the more friendly descriptions for the row and column headings in the tables. Title. Check this box to include the project description as the title in the Results pane. Logo. Check this box to display a company logo or other graphic at the top right of the Results pane. By default, the IBM Corp. logo is displayed. You can change this by creating your own logo or other graphic in.png file format and adding it to the location specified in the Table logo field on the File Locations tab. Note: Using this method adds the logo to all tables in the table document. An alternative method of adding a logo is to include the graphic in the header or footer for selected tables. For more information, see the topic Adding Hypertext Links and Images to Headers and Footers in Chapter 15 on p Headers and footers. Select this option if you want to display the headers and footers that have been defined for the table.

430 416 Chapter 18 Variable and category images. Select this option if you want to display images associated with table rows and columns. These may be images that were specified when the data was created using IBM SPSS Data Collection Interviewer Server, or they may be images that were added to your tables using IBM SPSS Data Collection Base Professional Tables Option. Horizontal variable text in side headings. Select this option to display text in the side headings horizontally, or deselect to display text vertically. Chart Properties: Chart series. Choose whether you want the table rows or columns to form the chart series. If you select the Chart category elements or Chart special elements box, ensure that the orientation of the categories or special items (in rows or columns) corresponds to the setting entered here. For example, to create a chart for a mean that appears on the top of a table, choose as columns. Chart category elements. You can optionally create charts for individual categories, for individual variables, or for all variables on the table. Select: Per element to create a separate chart for each category in the variable(s). Per variable to create a chart for each variable(s). Per table creates a single chart for all variables on the table. Chart special elements. You can optionally create charts for statistical items (such as the mean, minimum value, standard deviation, etc.). Select: Per element to create a separate chart for each statistical item in each variable. Per variable to create a chart for all statistical items in each variable. Per table creates a single chart for all statistical items in all variables on the table. Base chart on. If you want to base charts on a cell item other than the default, select the cell item from the drop-down list. The cell item must be included in the table. Display series base. Select this option to display the base for the chart series in the legend for the chart. Display base for last series category. Check this box to display the base for the last data point in the chart legend. This option is applicable only when charting special items. If the count cell item is present, this is used. If not, the unweighted count cell item is used. Chart percentages using scale of 0 to 100%. Check this box if you want percentages to be charted on a scale of 0 to 100%. If this option is not selected, the scale is based on the biggest value in the chart. HTML Properties: Use formatted labels. Select this option if you want to use HTML formatting in variable and category descriptions in a similar way to using HTML formatting in the headers and footers. The same set of HTML tags are supported and as in headers and footers, the HTML must be well-formed. For more information, see the topic HTML Formatting for Headers and Footers in

431 417 Customizing IBM SPSS Data Collection Survey Reporter Chapter 15 on p Typically you set up the formatting in the dit Variable dialog box before exporting. If you export to any of the other formats (or to HTML without using this option), any HTML tags in the variable or category descriptions will appear as plain text. Note that using this option may make the export run a little more slowly. For more information, see the topic Using HTML Formatting in Category Descriptions in Chapter 16 on p mbed style sheet. Select this option if you want to embed the style sheet within the HTML file. This is useful when you want to distribute the HTML output, for example, by . Insert printing page breaks. Select this option if you want to add a printing page break between tables when using the Single Document layout style. Note that this option does not insert a printing page break between tables and charts. Options: Size and Layout Tab Use the options in the Size and Layout tab to change the size of text and icons that appear in the IBM SPSS Data Collection Survey Reporter window. Fields on the Size and Layout Tab Font Size/Icon Size. Resize the font and the icons in various areas of the Survey Reporter window and the toolbar. Allow docking and undocking of window panes. Check this box if you want the panes in the Survey Reporter window, for example, the Notes pane or the Variables pane, to be unlocked so that they can be moved around the window. Deselect the box once you have arranged the panes to your satisfaction, to prevent accidental changes. Options: File Locations Tab Use the options in the File Locations tab to specify the folders used to store templates, images, and other files used by IBM SPSS Data Collection Survey Reporter. Note: The File Locations tab only applies to Survey Reporter, not IBM SPSS Data Collection Survey Reporter Server dition. In Survey Reporter Server dition, only the Black and White style sheet is installed. To customize the style sheet for Survey Reporter, you can create your own stylesheet (.css) and table logo and add it to the user s project folder, shared project folder, or shared folder. The priority is: 1. User project folder (for example: [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\Interviewer Server Administration\FMRoot\Users\admin\Projects\project1\Reporter\Styles\) 2. Shared project folder (for example: [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\Interviewer Server Administration\FMRoot\Shared\Projects\project1\Reporter\Styles\

432 418 Chapter Shared folder (for example: [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\Interviewer Server Administration\FMRoot\Shared\Reporter\Styles\) Note: Youmustfirst create the \Reporter\Styles subfolders. In Survey Reporter, only Black and White style provided with the installer. You can create your own stylesheet (.css) and add it to the user s project folder. To create a custom stylesheet: Launch the Survey Reporter application. Click Open From IBM SPSS Data Collection Interviewer Server Administration. Navigate into your local user folder and click anywhere in File Name dialog box to make the Create Folder option visible. Click Create Folder and create a new Reporter folder. Click the newly created Reporter folder, click Create Folder, and create a new Styles folder (Styles must be a sub-folder to Reporter). Click Upload to load your custom stylesheet. The stylesheet must be named defaultstyle.css. Click Upload to load your custom logo. The logo must be named defaultlogo.gif. You must close and relaunch Survey Reporter in order for the new style to be available. You can also use the IBM SPSS Data Collection Publish Assets Utility to deploy customized style sheets. Prepare your custom files in the Survey Reporter Server ditioncustom Files subdirectory (for example, C:\InetPub\wwwroot\SPSSMR\Reporter\Custom Files\Styles). Fields on the File Locations Tab Choose the Browse button beside an option, then select a folder or file from the Open dialog box to set that folder as the location where Survey Reporter looks for files of the selected type. In the case of the Table logo and Template file options, you must select a specific file of the appropriate type, not just a folder. Style templates. This is the location of the style sheet (.css) files that control the appearance of the Results tab. By default, style sheets are located in C:\Documents and Settings\All Users\IBM\SPSS\DataCollection\6\Survey Reporter\Styles. You can add your own style sheets to this folder, or you can change this location to point to another folder containing your own style sheets. For more information, see the topic Customizing the Format of Your Results on p Table logo. This is the name and location of an image file that displays a logo or other graphic on all your tables. The file must be in a.png file format. You can also turn the logo on or off using the Display logo option in the Display tab. Template file. This is the name and location of a template table document file that contains default settings for all new table documents that you create. By default, no template file exists and the Survey Reporter default settings are used. A template file is created automatically in when you choose the Save as Default option in the Table Properties dialog box. The default location is a

433 419 Customizing IBM SPSS Data Collection Survey Reporter sub-folder of the Documents and settings folderunderyouruser name, forexample, C:\Documents and Settings\<your Windows user name>\application Data\IBM\SPSS\DataCollection\6\Survey Reporter Youcanaddyourowntemplatefile to this folder and select it here, or you can browse to a template file in another folder. For more information, see the topic Customizing Table Document Templates on p Chart template location (Microsoft Office 2007 only). This is the name and location of a template file to be used for tables exported to Microsoft xcel Click Browse... to select a template from the xcel 2007 chart template folder or another location. IBM SPSS Data Collection Publish Assets Utility The IBM SPSS Data Collection Publish Assets Utility and the command-line Publish Assets Utility allows you to manage your customized files for web-deployed IBM SPSS Data Collection products (for example, IBM SPSS Data Collection Author Server dition, IBM SPSS Data Collection Survey Reporter Server dition. Running the IBM SPSS Data Collection Publish Assets Utility Backup the appropriate web-deployed applications that are installed on your workstation (for example, if you have installed Survey Reporter Server dition, backup the directory C:\InetPub\wwwroot\SPSSMR\Reporter). Prepare your custom files in the web-deployed application s sub-directory Custom Files (for example, for Survey Reporter Server dition, the sub-directory is C:\InetPub\wwwroot\SPSSMR\Reporter\Custom Files). Run the Publish Assets Utility (PublishAssetsUI.exe). The utility is installed with Survey Reporter Server dition at: C:\InetPub\wwwroot\SPSSMR\Reporter.

434 420 Chapter 18 Figure 18-5 Publish Assets Utility Click Browse... next to the Application Name field and select the appropriate *.application file (for example, Author.application for Author Server dition or Reporter.application for Survey Reporter Server dition). If necessary, increase the Revision number (the number automatically increments by one). Click Browse... next to the Path field and select your Personal Information xchange (.pfx) file. The file is used to sign the manifest. If necessary, enter an appropriate password in the Password field. Click Browse... next to the Custom Files Path field and select the Custom Files directory for the appropriate web-deployed application. The directory contains the custom files that you want to deploy. Click Save to deploy your custom files. The command-line IBM SPSS Data Collection Publish Assets Utility The command-line Publish Assets Utility (PublishAssets.exe) provides command-line options that serve the same function as the Publish Assets Utility.

435 421 Customizing IBM SPSS Data Collection Survey Reporter Table 18-1 Switched and arguments Parameter -AppManifest <path> -appm -CustomFolder <path> -CertFile <path> -Password -pwd -RevVersion <version> -Help -? -h Description Optional. The application s manifest file. By default, the first *.application file in current directory is searched. Optional. The custom files folder. The default location is the Custom Files folder in the current directory. Required. A Personal Information xchange (.pfx) file contains a public key and a private key. The file is used to sign the manifest file. Optional. The password for the.pfx file (if required). Optional. The revision version to publish for the application. By default, the value is incremented by one. Help for the utility. Running the Publish Assets Utility for Survey Reporter Server dition The Publish Assets Utility executablefile PublishAssets.exe is located in the directory where Survey Reporter Server dition is installed (the default directory is C:\InetPub\wwwroot\SPSSMR\Survey Reporter). Table 18-2 Supported custom files File\Directory Name Reporter.exe.config Styles Description The application s configurations file. Directory that contains the style sheet (.css) files. Obtaining a Personal Information xchange (.pfx) file You must provide a Personal Information xchange (.pfx) file in the Publish Assets Utility in order to protect your deployed files. The following files are required to generate a.pfx file: Apublickey(.cer) file A private key (.pvk) file If you do not have these files, you can use the Microsoft Certificate Creation Tool makecert.exe (available in the Microsoft Windows SDK). The tool is intended for testing purposes. For example: makecert.exe -sv MyKey.pvk -n "CN=MyCompanyName" MyKey.cer You will be prompted to provide a password for the private key. When you have your public key (.cer) and private key (.pvk) files, you can then generate a Personal Information xchange (.pfx) file by using the Microsoft PVK/SPC to PFX file converter pvk2pfx.exe. For example: pvk2pfx.exe -pvk MyKey.pvk -spc MyKey.cer -pfx MyPFX.pfx -po MyPassword Note: You can obtain the makecert.exe and pvk2pfx.exe utilities from the Microsoft Windows SDK or Microsoft Windows Drive Kit.

436 Reference Chapter 19 This section contains additional reference information about IBM SPSS Data Collection Survey Reporter. Table Specification Syntax This section provides full details of the table specification syntax. In most cases, you can create tables without needing to understand the syntax, but for particularly complex tables, you can enter or edit the syntax directly, in the Table Syntax pane, the Filter Syntax pane or the Script pane in the New Variable, dit Variable, or dit Table Variable dialog boxes. You can also type expressions directly in the dit Derived Category dialog box and the Create New Variable Based On dialog box. Detailed documentation on how to write scripts to generate tables is provided in the Data Collection Developer Library (DDL) Note on terminology In this section, the terminology used is based on that in the Table Object Model. The following table relates a number of Table Object Model words and phrases to the equivalent features in the IBM SPSS Data Collection Survey Reporter user interface. Table Object Model Axis Axis expression lement Special element Concatenation Survey Reporter Thesideortopofatable dits made to a variable A category in a variable, or one of the other items that can appear in a variable such as a mean, subtotal, etc. Term used specifically to refer to the non-categorical items in a variable, such as a mean, subtotal, etc. Adding multiple variables to the side or top of a table one after the other, without nesting. Table and Axis Syntax This topic provides a detailed description of the syntax you use to specify tables in a script. Table Specification Atablespecification consists of up to two axis specifications that define the side and top of the table in order as follows: <table-spec> ::= [<axis-spec>] [* <axis-spec>] Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

437 423 Reference These axis specifications (sometimes called the root-level axes) define the dimensions of the table. The axis specification on the left of the * defines the side axis, which in turn defines the rows of the table. The axis specificationontherightofthe*definesthetopaxis,whichinturndefines the columns of the table. IBM SPSS Data Collection Survey Reporter supports two table dimensions (side and top). Axis Specification <axis-spec> ::= <axis> <axis> ::= <axis> > <axis> <axis> + <axis> (<axis>) id as AxisName id ['label-text'][as AxisName] id [LanguageID:'label-text'][as AxisName] id {<element-list>} [MaxResponses = Value][as AxisName] axis (id) axis ( {<element-list>} [MaxResponses = Value]) axis ( {<element-list>} [MaxResponses = Value]) as AxisName Part Description > Indicates that the axis on the right of the > symbol is to be nested within the axis on the left of the symbol. Generally the evaluation of the axis specification takes place from left to right. However, when an axis specification contains both > and + symbols, the > symbol takes precedence over the +. (This means that the > symbol is evaluated before the + symbol.) However, you can use parentheses to change the order of precedence. + Indicates that the two axes separated by the symbol are to be concatenated. () Parentheses used to indicate that the symbols within the parentheses are to be evaluated before the symbols outside the parentheses. id Indicates that the axis is to be created from the variable with name id. If an axis expression has been defined in the metadata (in the Axisxpression property), it is used to define the elements. What happens if an axis expression has not been defined in the metadata depends on the variable type. For a categorical variable, all of the elements within the variable are used. For numeric, text, date, and Boolean variables, you will get an error. id {<element-list>} Indicates that the axis is to be created from the variable with name id and the elements are to be as specified in the element list. You can define new analysis elements in the element list. For more information, see the topic lement List Syntax on p axis (id) Indicates that the axis is to be created from a reusable axis with name id. A reusable axis is an axis that has been added to the Document.Axes collection.

438 424 Chapter 19 Part id as AxisName axis ( {<element-list>}) axis ( {<element-list>}) as AxisName [MaxResponses = Value] Description Indicates that the axis is to be created from the variable with name id, but that the axis will have the name AxisName. Use this if you want to add the same variable to an axis more than once. Indicates that the axis is to be created without reference to an existing variable. The base for the new variable contains all cases. If you do not specify an axis name, the axis is given the default name of _Custom. If you want to create more than one axis, you should give each one a unique name. Creates an axis without reference to an existing variable, and saves it with a unique name. Custom property for axis. When using axis expressions to edit a variable, the max response value could be changed. For example, an axis expression can change a single response variable to a multiple response by doing a net and keep operation. It is important to identify when a variable, or an axis, is single or multiple while performing statistic tests, as they may require different formulas. You should set the appropriate value when the response type is different from the variable. Note: Do not take statistics elements into account. xamples The following table provides some example table specifications. Table specification: Creates a table that has: age a side axis only, based on a single variable called age. * age a top axis only, based on a single variable called age age * gender asideaxisbasedontheage variable and a top axis based on the gender variable. interest * axis(mybanner) a side axis based on a single variable called interest and a top axis based on the reusable axis called MyBanner. age + gender * interest > before a side axis based on the variables called age and gender concatenated together and a top axis that is based on the variable called before nested inside the variable called interest. interest * resident + axis(mybanner) a side axis based on a single variable called interest and a top axis based on a variable called resident concatenated with a reusable axis called MyBanner. interest{dinosaurs, Fossils, Whales} * gender a side axis based on three specific elementsofa variable called interest and a top axis based on a variable called gender. For more information, see the topic lement List Syntax on p age 'Age Range' + gender a side axis only, based on a variable called age with the label Age Range concatenated with a variable called gender with the default label.

439 425 Reference Table specification: age NU: 'Age Range' SN: 'dad' education as education1 > gender + education as education2 > biology axis({base(), male expression('gender={male}')}) axis({base(), male expression('gender={male}')}) as MyMaleAxis order{first, second} * order[..].column Creates a table that has: a side axis only, based on a variable called age with labels in United States nglish (NU) and International Spanish (SN). For languages where no label is specified, the default label from the metadata is used. For details of recognized language codes, see Languages (3-Character Codes). a side axis only, based on a variable called education which is used twice in the axis, once with gender and once with biology nested within it. a side axis only, with the default name _Custom. The axis is not based on an existing variable. a side axis only, with the name MyMaleAxis. The axis is not based on an existing variable. demonstrates editing grid and loop iterations. lement List Syntax The Table and Axis Syntax topic describes the syntax that you use to define the axes of your tables. One of the options is to use an element list to specify the elements that are to be included. The term element includes categories, user-defined categories, means or other statistics, and any other item that forms part of a variable (in the IBM SPSS Data Collection Survey Reporter user interface, the term category is used to refer to all of these items for the sake of simplicity, but strictly speaking they are elements). ach element is usually displayed as a row or column on a table (though in some cases the element may be included in the table but not displayed). The element list syntax is: VariableName {<lement-list>} <lement-list> ::= <lement> (, <lement>)* <lement> ::= [^] lementname ['Label-text'] [<Properties>] lementname ([LanguageID: 'Label-text'])* [^][lementname].. [lementname] <Special-lement> Part Description VariableName Thenameofavariable in the metadata. lementname The name of an element in the specified variable. ^ Indicates that the following item is to be excluded... Indicates a range of elements. LanguageID The code of a language that exists in the metadata. For details of recognized language codes, see Languages (3-Character Codes).

440 426 Chapter 19 Part <Special-lement> <Properties> Description Defines a special non-category element. For more information, see the topic lement Syntax on p Defines one or more properties for the element. For more information, see the topic lement Property Syntax on p The list of elements is evaluated from left to right and determines the order in which the elements appear in the axis. lement Names Do not use the default names of special elements as element names unless you are creating a special element. If you are creating multiple elements, ensure that the element names are unique. xamples The following examples are based on the interest variable in the Museum sample data set. The interest variable has the following elements: Position lement Name 1 Dinosaurs 2 Conservation 3 Fish_and_reptiles 4 Fossils 5 Birds 6 Insects 7 Whales 8 Mammals 9 Minerals 10 cology 11 Botany 12 Origin_of_species 13 Human_biology 14 volution 15 Wildlife_in_danger 16 Other 17 Not_answered 1. Single elements interest{whales, Fossils, Dinosaurs} This creates an axis that has three elements from the interest variable in the order Whales, Fossils, Dinosaurs. 2. All elements from the first to a specified element

441 427 Reference interest{.. Whales} This creates an axis that has a range of elements from the first element in the variable s element list through the Whales element (which in this example is the seventh element in the variable). The elements appear in the order in which they appear in the variable (Dinosaurs, Conservation, Fish_and_reptiles, Fossils, Birds, Insects, Whales). 3. All elements from a specified element to the last element interest{whales..} This creates an axis that has a range of elements from the Whales element through the last element in the variable s element list. The elements appear in the order in which they appear in the variable (Whales, Mammals, Minerals, cology, Botany, Origin_of_species, Human_biology, volution, Wildlife_in_danger, Other, Not_answered). 4. A range of elements interest{whales..botany} This creates an axis that has an element list starting with the Whales element and ending with the Botany element and including all of the elements in between (Whales, Mammals, Minerals, cology, Botany). 5. All elements interest{..} This creates an axis that has all of the elements in the variable in their default order. Although this syntax is not generally used on its own, it is useful when you want to exclude categories from the list as shown in the next example, or add special elements to the list of elements. For more information, see the topic lement Syntax on p All elements except those in a specified range interest{.., ^Other..Not_answered} This creates an axis that has all of the elements in the variable in their default order with the exception of any elements in the list from Other through Not_answered. (Theelementsthat are included are Dinosaurs, Conservation, Fish_and_reptiles, Fossils, Birds, Insects, Whales, Mammals, Minerals, cology, Botany, Origin_of_species, Human_biology, volution, and Wildlife_in_danger.) 7. All elements in a range with the exception of one specified element interest{dinosaurs..whales, ^Conservation} This creates an axis that has all of the elements in the variable from Dinosaurs through Whales with the exception of the Conservation element. (The elements that are included are Dinosaurs, Fish_and_reptiles, Fossils, Birds, Insects, andwhales.) 8. Specified elements using custom labels

442 428 Chapter 19 interest{dinosaurs 'xtinct reptiles', Whales 'Large marine mammals'} This creates an axis that has two elements (Dinosaurs and Whales). However, instead of using the standard labels stored in the metadata for the current language, user context, and label type, the elements will have labels of xtinct reptiles and Largemarinemammals, respectively. These custom labels will be used for the current language, user context, and label type only. If you change the language, user context, or label type, the label stored in the metadata for the selected language, user context and label type will be used. However, if you return to the original language, user context, and label type, the custom labels will be used again. When you specify a custom label, you need to enclose the label text in single quotation marks ( <label text> ) or two double quotation marks ( <label text> ). If you use single quotation marks, you must escape any single or double quotation marks included in the label with a second quotation mark of the same type. This indicates that the quotation mark used in the label does not represent the end of the label. If you use two double quotation marks, you need to escape any double quotation marks used in the label with three double quotation marks. 9. Custom labels in multiple languages interest{dinosaurs NU:'xtinct reptiles' SN:'Reptiles extintos', Whales NU:'Large marine mammals' SN:'Mamíferos marinos grandes'} This creates an axis that has the same two elements (Dinosaurs and Whales) as in the previous example. However, this time custom labels have been defined for two languages (NU United States nglish and SN International Spanish). These labels will be used for the specified languages only and if you select another language, the label stored in the metadata for that language will be used. lement Syntax The lement List Syntax topic describes the syntax that you use to specify the elements to include in the axis of a table. This topic documents the special elements that you can include in an axis. By default, the element name is the same as the element type. For example, by default, a Standard rror element is called stderr. However, if you create multiple elements of the same type, you must specify names to ensure that each element is uniquely identified. The following table provides a summary of the syntax for each element type. The majority of these items can also be added using the Insert Categories dialog box. The Combine and Net elements can be added using the relevant options on the dit Variable menu. Description Base Unweighted base Mean Standard deviation Standard error Sample variance Syntax base([ xpression Text ]) unweightedbase([ xpression Text ]) mean([numericvariable], [ xpression Text ]) stddev([numericvariable], [ xpression Text ]) stderr([ NumericVariable ], [ xpression Text ]) sampvar([numericvariable], [ xpression Text ])

443 429 Reference Description Total Subtotal Text (Subheading) Syntax total() subtotal() text() Minimum min(numericvariable, [ xpression Text ] ) Maximum max(numericvariable, [ xpression Text ] ) Net Combine xpression (User-defined category) net({lementlist}) combine({lementlist}) expression('xpressiontext') Numeric numeric(numericvariable, [ xpression Text ] ) Paired Preference Derived derived( xpression Text ) Sum sum(numericvariable, [ xpression Text ]) ffective base ppt() effectivebase() Median median(numericvariable, [ xpression Text ] ) Percentile percentile(numericvariable, CutOffValue, [ xpression Text ]) Mode mode(numericvariable, [ xpression Text ] ) Net Difference ntd() Note: NumericVariable (AnalysisVariable), Multiplier, and Weight properties need to be specified as absolute references. However, variable references in expressions need to be specified as relative references. Using the Household.mdd sample as an example, when editing a categorical variable at the person level, if you want to display the mean of man s weight, you can add the following mean element: mean(person[..].weight, 'gender.containsany({male})') Note on Naming Nets When you create a net, if the name of the net is the same as that of any of the categories in the net, a net expression will be generated on the category, which will slow performance. Because of this, it is recommended that you do not use the same name for a net as for any of the categories in the net (though you can use the same description). For example, instead of: Blue 'Blue' net({blue, PaleBlue, DarkBlue}) use: Blue_net 'Blue' net({blue, PaleBlue, DarkBlue}) lement Property Syntax You can define properties for elements and special elements in the axis specification. You specify the properties after the element to which they apply as follows: <properties> ::= [<property> [, <property>]] <property> ::= CalculationScope=Alllements Precedinglements CountsOnly=True False

444 430 Chapter 19 Decimals=DecimalPlaces Factor=FactorValue IsFixed=True False IsHidden=True False IsHiddenWhenColumn=True False IsHiddenWhenRow=True False IncludeInBase=True False IsUnweighted=True False Multiplier=MultiplierVariable Weight=WeightVariable These properties can also be set using the Properties pane in the dit Variable dialog box. Languages (3-Character Codes) The following table shows the 3-character language codes for many of the world s languages. Code AFK SQI ARG ARH AR ARI ARJ ARK ARB ARL ARM ARO ARQ ARA ARS ART ARU ARY HY UQ BL BGR CAT CHS ZHH ZHI CHT HRV CSY Language Afrikaans Albanian Arabic - Algeria Arabic - Bahrain Arabic gypt Arabic Iraq Arabic Jordan Arabic Kuwait Arabic Lebanon Arabic Libya Arabic Morocco Arabic Oman Arabic Qatar Arabic Saudi Arabia Arabic Syria Arabic Tunisia Arabic United Arab mirates Arabic Yemen Armenian Basque Basque Belarusian Bulgarian Catalan Chinese Chinese Hong Kong, SAR Chinese Singapore Chinese Taiwan Croatian Croatia Czech

445 431 Reference Code DAN NLB NLD NA NL NC NB NI NJ NZ NS NT NG NU TI FOS FAR FIN FRB FRC FRA FRL FRS DA DU DC DL DS LL HB HIN HUN ISL IND ITA ITS JPN KOR LVI LTH MSL NOR NON PLK Language Danish Dutch Belgium Dutch The Netherlands nglish Australia nglish Belize nglish Canada nglish Caribbean nglish Ireland nglish Jamaica nglish New Zealand nglish South Africa nglish Trinidad nglish United Kingdom nglish United States stonian stonia Faroese Faroe Islands Farsi Finnish French Belgium French Canada French France French Luxembourg French Switzerland German Austria German Germany German Liechtenstein German Luxembourg German Switzerland Greek Hebrew Hindi Hungarian Icelandic Indonesian Italian Italy Italian Switzerland Japanese Korean Latvian Lithuanian Malay Malaysia Norwegian (Bokmal) Norwegian (Nynorsk) Polish

446 432 Chapter 19 Code PTB PTG ROM RUS SRB SRL SKY SLV SS SB SL SO SC SD SF S SG SH SM SI SA SZ SR SU SY SV SVF SV THA TRK URK URD VIT Language Portuguese Brazil Portuguese Portugal Romanian Romania Russian Russia Serbian (Cyrillic) Serbian (Latin) Slovak Slovenian Spanish Argentina Spanish Bolivia Spanish Chile Spanish Colombia Spanish Costa Rica Spanish Dominican Republic Spanish cuador Spanish l Salvador Spanish Guatemala Spanish Honduras Spanish Mexico Spanish Nicaragua Spanish Panama Spanish Paraguay Spanish Peru Spanish Puerto Rico Spanish Uruguay Spanish Venezuela Swedish Finland Swedish Sweden Thai Thailand Turkish Ukrainian Urdu Vietnamese Vietnam Naming Conventions Names of variables, categories and other elements of a variable, and filters must conform to the following rules: The first character must be a letter or the _ (underscore) symbol. Subsequent characters can be: Letters.

447 433 Reference Decimal numbers from either Basic Latin or other national scripts. mbedded spaces and special characters are not allowed. A letter is any nglish letter character (a-z, A-Z) or a letter character from another language. Reserved Words Prior to IBM SPSS Data Collection version 6.0.1, the following keywords were reserved. Starting with version 6.0.1, the following words can be used for the names of variables, elements, or filters. Add Date Group Nonamespace Row All Dateonly Having Null Select Alter Default Hdata Object Set Alternatives Define Helperfields On Stddev Area Delete Info Order Step As Desc Insert Other Sum Asc Descending Into Otherspecify Style Ascending Double Item Parentquestion Table Avg Drop Label Precision Text Axis lementtype Labeltypes Properties Timeonly Base nd Languages Protected True Block rrors Layouttemplate Questionfullname Truncate Boolean xclusive Lcl Questioninfo Type By xec Level Questionname Update Categorical xpand Long Questiontype Usagetype Categories xpression Loop Ran Use Column False Metadata Randomize Validation Compound Fields Max Rev Value Contexts Fix Min Reverse Values Count From Namespace Rot Where Create Grid Nocasedata Rotate With Function List This section contains a listing of all the functions in the IBM SPSS Data Collection Function Library. For full details and examples of usage, see the Data Collection Function Library topics in the IBM SPSS Data Collection Scripting section of the IBM SPSS Data Collection Developer Library. Categorical Functions Function AnswerCount(Val) Description Returns the number of categories selected in a category list.

448 434 Chapter 19 Function Description ContainsAll(Val, Answers [, xactly]) Identifies whether a category list contains all of the categories in a given list. ContainsAny(Val, Answers [, xactly]) Identifies whether a category list contains one or more categories in a given list. ContainsSome(Val, Answers [, Min] Identifies whether a category list contains some of [, Max] [, xactly]) the categories in a given list. DefinedCategories(Val [, Answers]) Returns a set of categories of a categorical variable. Definedlements(Val [, Types]) Returns a set of elements of a categorical variable. DefinedFactors(Val [, Answers]) Returns a set of factor numbers as definedonthe categories in a variable. DefinedListlements(Val, Answers [, Types])Returns a set of elements of a categorical variable. Difference(Val, Answers) Returns the difference of two category lists that is, it returns the categories that are in the first category list but not in the second. Factor(Val) Returns the factor defined for an element of a categorical variable. GetAnswer(Val, Index) Returns a specified category in a category list. HasAnswer(Val, Answer) Identifies whether a specified category is in a category list. Intersection(Val [, Vals,...]) Returns the intersection of two or more category lists that is, it returns the categories that appear in all of the category lists. LBound(List [, Dimension]) Returns the smallest available subscript for the indicated dimension of an array. By default, the lower bound is returned for the first dimension of the array. Merge(Vals) Returns the union of a number of categorical values; that is, returns the categories that are in any of the input categorical values. ReDim(List, Size [, Preserve]) Re-sizes an array to a given size. By default, the array contents are preserved. UBound(List [, Dimension]) Returns the largest available subscript for the indicated dimension of an array. By default, the upper bound is returned for the first dimension of the array. Union(Val [, Vals,...]) Returns the union of two or more category lists that is, it returns all of the categories that are in one or more of the category lists. Unique(Val) Returns a category list with any duplicate categories removed. XUnion(Val, Answers) Returns the exclusive union of two category lists that is, it returns all of the categories that are in either one of the category lists, but not in both. Text or Categorical Functions Function Find(Val, Key [, Skip [, Reverse]]) Description Searches a string or category list for a specified substring or subcategory list, and if it is found, returns its start position. Note that the search is case insensitive.

449 435 Reference Function Left(Val, Length) Len(Val) Mid(Val, Start [, Length]) Right(Val, Length) Description Returns either a string containing the first characters from a string, or a category list containing the first categories from category list. Returns a Long containing the number of characters in a string or the number of categories in a category list. Returns either a string containing a specified number of characters from a specified position in a string, or a category list containing a specified number of categories from a specified position in a category list. Returns either a string containing the last characters from a string, or a category list containing the last categories from category list. Text Functions Function AscW(Val) ChrW(Val) Format(Val [, Style [, Width [, Locale]]]) Hex(Val) LCase(Val) LTrim(Val) MakeMDMName(Val) MakeString(Vals) Oct(Val) RTrim(Val) Split(Val [, Delimiter [, Count ]]) Trim(Val) UCase(Val) Description Returns an integer value representing the Unicode character code for a character. Returns the character that corresponds to a given Unicode character code. Returns a string that is the result of formatting a value according to a specified style. Returns a string representing the hexadecimal value of a number. Returns a string that has been converted to lower case. Returns a copy of a string with leading spaces removed. Replaces characters that are not allowed in the name of an MDM object, to produce a valid name. Returns a text string by concatenating one or more values. Returns a string representing the octal value of a number. Returns a copy of a string with trailing spaces removed. Returns an array that contains substrings. Returns a copy of a string with both leading spaces and trailing spaces removed. Returns a string that has been converted to upper case. Date and Time Functions Function DateAdd(Val, Interval, Count) DateDiff(Val1, Val2, Interval) Description Returns a date to which a specified time interval has been added. Returns the time interval between two dates.

450 436 Chapter 19 Function DateNow([ Val [, IgnoreDaylightSaving]]) DateOnly(Val) DatePart(Val, Interval) Description Returns the current local date in a particular time zone. Returns the date from a date and time value. Returns a specified part of a given date. Day(Val) Returns a whole number between 1 and 31, inclusive, representing the day of the month. GetTimeZone([Val]) Returns the index value of a time zone defined in the registry on the server. GetTimeZoneDaylightSaving([Val [, Time]]) GetTimeZoneName([Val]) GetTimeZoneOffset([Val [, Time [, IgnoreDaylightSaving]]]) Returns True if daylight-saving is currently in effect at the specified time in the specified time zone, or False if not. Returns the name of the local time zone. Returns the number of minutes to add to or subtract from UTC time to get the local time. Hour(Val) Returns a whole number between 0 and 23, inclusive, representing the hour of the day. LocalToUTCTime(Val [, Zone [, IgnoreDaylightSaving]]) Returns the UTC time that corresponds to a given local time. Minute(Val) Returns a whole number between 0 and 59, inclusive, representing the minute of the hour. Month(Val) Returns a whole number between 1 and 12, inclusive, representing the month of the year. MonthName(Val [, Abbreviate [, Locale ] ]) Returns a string indicating the specified month. Now([ Val [, IgnoreDaylightSaving]]) Returns the current local date and time in a particular time zone. Second(Val) Returns a whole number between 0 and 59, inclusive, representing the second of the minute. SetTimeZone(Val) Sets the time zone for a program. TimeNow([ Val [, IgnoreDaylightSaving]]) Returns the current local time in a particular time zone. TimeOnly(Val) Returns the time from a date and time value. UTCToLocalTime(Val [, Zone [, IgnoreDaylightSaving]]) WeekdayName(Val [, Abbreviate [, Locale ] ]) Year(Val) Returns the local time that corresponds to a given UTC time. Returns a string indicating the specified day of the week. Returns a whole number representing the year. Conversion Functions Function CBoolean(Val) CCategorical(Val) CDate(Val) CDouble(Val) CLong(Val) CText(Val) Description Converts a value of any data type to a Boolean value. Converts a value of any data type to a Categorical value. Converts a value of any data type to a Date value. Converts a value of any data type to a Double value. Converts a value of any data type to a Long value. Converts a value of any data type to a Text value.

451 437 Reference Random Number Functions Function GetRandomSeed() RanInt([Seed]) Rnd([Seed]) SetRandomSeed([Seed]) Description Returns the current starting point of the random number generator. Returns a random integer number. Returns a random decimal number. Sets the starting point for the random number generator. List Functions Function FindItem(List, Key) GetReversalSeed() GetRotationSeed() Ran(List [, Count [, Seed]]) RanSequence(Start, nd [, Step [, Count[, Seed]]]) Rev(List [, Count [, Policy [, Seed]]]) RevSequence(Start, nd [, Step [, Count[, Policy[, Seed]]]]) Rot(List [, Count [, Policy [, Seed]]]) RotSequence(Start, nd [, Step [, Count[, Policy[, Seed]]]]) SelectRange(List [, Range [, Count]]) SetReversalSeed([Seed]) SetRotationSeed([Seed]) SortAsc(List [, Count [, IgnoreLocale]]) SortDesc(List [, Count [, IgnoreLocale ]]) Description Returns a specified item from a list, or NULL if the item isn t found. Returns the current reversal state (which is used by the Rev function). Returns the current rotation state (which is used by the Rot function). Returns a randomized copy of a list. An optional parameter defines how many items from the input list are included in the randomized list. Returns an array containing values selected randomly from a given series of integers. Returns an array containing copies of items from an input list, either in the normal order or in reverse order. The optional Count parameter defines how many items from the input list are included in the returned list. Returns an array containing values selected from a given series of integers, either in the original order or in reverse order. Returns an array containing copies of items from the input list, in a rotated order. The optional Count parameter defines how many items from the input list are included in the returned list. Returns an array containing values selected from a given series of integers in a rotated order. Returns an array containing copies of selected items from the input list. Sets the reversal state. Sets the rotation state. Returns an array containing copies of items from the input list, sorted in ascending order. The optional Count parameter defines how many items from the input list are included in the returned list. Returns an array containing copies of items from the input list, sorted in descending order. The optional Count parameter defines how many items from the input list are included in the returned list.

452 438 Chapter 19 Mathematical Functions Function Abs(Val) Atn(Val) Cos(Val) xp(val) Int(Val) Log(Val [, Base]) MaxOf(Val1 [, Vals,...]) MinOf(Val1 [, Vals,...]) Pow(Val1, Val2) Round(Val [, Digits [, Policy]]) Sgn(Val) Sin(Val) Sqrt(Val) Tan(Val) Description Returns the absolute value of a number. Returns the arctangent of a number. Returns the cosine of an angle. Returns e (the base of natural logarithms) raised to a power. Returns the integer portion of a number. Returns the logarithm of a number. Returns the maximum of two or more values. Returns the minimum of two or more values. Returns the value of a number raised to a power. Returns a number rounded to a specified number of decimal places or significant digits. Returns an integer that indicates the sign of a number. Returns the sine of an angle. Returns the square root of a number. Returns the tangent of an angle. Miscellaneous Functions Function Band(Val, Min, Size [, Count]) BitAnd(Val1 [, Vals,...]) BitNot(Val) BitOr(Val1 [, Vals,...]) BitXor(Val1 [, Vals,...]) CreateObject(Class) DBNull() ngineversion([val [, Number]]) qualband(val, Count, Min, Max) val(xpr) xecute(script) GetInterface(Object, InterfaceID) IIf(Val, TruePart, FalsePart) Description Calculates categories (called bands) foranumeric variable and returns the appropriate category for a specified value in the numeric variable. Performs a bitwise AND on two or more numeric values and returns the result. Performs a bitwise NOT on a numeric value and returns the result. Performs a bitwise OR on two or more numeric values and returns the result. Performs a bitwise XOR on two or more numeric values and returns the result. Creates and returns a reference to an Automation object. Returns a NULL data value for use with ADO. Returns part or all of the engine s version number. Calculates a specified number of equal categories (called bands) for a numeric variable and returns the appropriate category for a specified value in the numeric variable. valuates an expression and returns the result. xecutes one or more specified statements. Returns an alternate interface for an object. Returns the value passed as the TruePart parameter if the expression evaluates to True, otherwise returns the value passed as the FalsePart parameter.

453 439 Reference Function InputBox(Prompt[, Default[, Title]]) IsDBNull(Val) IslementInVersions(Val, lem, Versions) Ismpty(Val) IsqualObject(Val1, Val2) IsNullObject(Val) IsOneOf(Val1 [, Vals,...]) IsSet(Val, Mask) Replace(Val, Key, Replacement [, Start [, Count [, IgnoreCase]]]) RGB(Red, Green, Blue) Shellxecute(File [, HWnd [, Verb [, Parameters [, Directory [, ShowCmd]]]]]) Description Displays a dialog box containing a specified message, a text box for input, an OK button, and a Cancel button. Returns true if a value is a NULL data value that canbeusedbyado. Tests whether an element or list exists in all specified versions of a variable. Returns True if the value is empty. A string containing no characters or just containing white spaces is considered to be empty. A category list containing no categories is considered to be empty. All other data types are always considered to be not empty. Returns True if two values refer to the same object. Returns true if an variable is NULL, without testing the default property of the object being referenced. Returns true if a value is equal to at least one of the other listed values. Returns True if an integer value matches a specified mask. Replaces part of a text or categorical value with another value of the same type. Returns a number representing an RGB color value. Performs an operation on a specified file. Sleep(Val) Suspends the thread in which it is called. Validate(Val [, Min [, Max [, xpr [, Describe Validates ] a specified value based on specified ] ] ]) minimum and maximum values and optionally a validating expression. VarType(Val) Returns a numeric value indicating the subtype of avariable. VarTypeName(Val) Returns a string indicating the subtype of a variable. Multi-wave studies IBM SPSS Data Collection Survey Reporter can be used to analyze data from tracking or multi-wave studies. The purpose of a tracking study is to repeatedly measure the same variables and determine their changes over time. For example attitudes, awareness, or buying habits can be measured every month in a consistent fashion. In IBM SPSS Quantum /IBM SPSS Quanvert such projects are referred to as multi-wave projects. While the questions for each wave of a tracking study are consistent, they are not exactly the same. From wave to wave, questions and categories can be added or removed. For example, if a new brand comes onto the market, the brand would be added to the brand list. Similarly, the analyst may decide, that based on the analysis for the waves to date, additional questions are required for greater customer insight.

454 440 Chapter 19 Survey Reporter allows you move from one wave of the study to the next without having to recreate the variable edits and table definitions: Variable edits are retained. Variable edits are changes to the variable that do not result in the variable axis expression changing (for example, when the variable label is updated). Variable edits are retained without impacting changes to the variable s element list. Variable axis expressions are retained. Axis expressions on a variable are used to change how the elements for the variable are tabulated. For example, an axis expression can be used to hide, combine, or net elements. The axis expression can also be used to add new elements, such as user-defined and statistic elements. You can control whether changes to the element list, from one wave to the next wave, will be automatically reflectedintheaxis expression. lements added in a wave will also be added to any variable axis expressions. In some cases, such as variables edited to only show certain brands, automatically adding new elements may not be desired. Table edits are retained. Similar to axis expressions on variables, axis expressions can be added to a variable as part of a table definition. Table axis expressions are not updated to reflect the variable definitions in the latest wave. For example, if an element has been added to a variable and that variable has been edited on the table, the new element will not be included in the table. However, if the variable has not been edited on the table, the new element is included. Rounding in IBM SPSS Data Collection Survey Reporter IBM SPSS Data Collection Survey Reporter performs all calculations using the maximum possible accuracy and only performs rounding immediately before it displays figures in a table. Survey Reporter uses a standard rounding algorithm when it performs rounding. When rounding a real number to an integer, for example, Survey Reporter rounds to the nearest integer, except where the decimal places are exactly 5. In these cases, it rounds to the even integer by default. This means that of the two possible rounded values, the one that has an even number as the last significant digit is returned. For example, is rounded to 15.2 rather than If you want to instead round half values up, you can set the RoundingOptions property to 1. Refer to the topic Table Properties in the Data Collection Developer Library for more information. Apparent anomalies when you change the accuracy of cell contents that are real numbers can usually be explained by the fact that Survey Reporter performs each rounding calculation separately using the maximum possible accuracy. For example, when you display a weighted count of with one decimal place, it is shown as If you then choose to display it without decimal places, it becomes 51. Atfirst sight, you might think this is incorrect because 51.5 should be rounded to the even number 52. However, Survey Reporter performs each rounding calculation separately from the unrounded value, which in this example is , and the figure of 51 is in fact correct. During the calculation of a base in a weighted table (for example, from counts for use in a percentage calculation), Survey Reporter uses the maximum possible accuracy of the contributing values. If the base is subsequently displayed in the table, Survey Reporter rounds it to the same number of decimal places as the counts. This means that sometimes a base displayed in a table is not exactly equal to the sum of the counts displayed in the contributing cells. For example,

455 441 Reference the following table shows the values both before and after rounding of the counts for two cells and the base that Survey Reporter calculates: Cell Value before rounding Value shown in table Base When you show row or column percentages in a table, Survey Reporter can optionally manipulate the percentages to eliminate anomalies such as these. You can do this by selecting Adjust rounding so that percentages add up to 100% in the Display tab of the Table Properties dialog box. Note:IBM SPSS Statistics calculates table totals from the rounded values shown in the table. In a corresponding SPSS Statistics table containing the same figures, the total would be shown as 7. Formulae for Cell Contents This topic provides the formulae used by IBM SPSS Data Collection Survey Reporter to calculate the various types of cell contents. The topic is divided into two subsections. The first provides the formulae used to calculate the cell contents that are not dependent on a numeric variable and the second provides the formulae for the summary statistics of numeric variables. Notation The following table shows the notation used in this topic except where stated otherwise. Notation Description Sum of cell weights for cases in cell (i, j). Number of rows contributing to the test Number of columns contributing to the test The jth column subtotal: The ith row subtotal: The grand total:

456 442 Chapter 19 The following table provides the formulae used by Survey Reporter to calculate the cell contents that are not dependent on a numeric variable. Item Count Formula Column Percentage Row Percentage Total Percentage Indice xpected Count Residual Summary Statistics of Numeric Variables Notation The following table shows additional notation used in the remainder of this topic except where stated otherwise. Notation Description Value of the variable for case i. Weight for case i Number of cases Sum of the weights for the first i cases Mean for the first i cases

457 443 Reference The following table provides the formulae used by Survey Reporter to calculate the cell contents that are dependent on a numeric variable, with the exception of percentiles, the formula for which is shown below the table. Item Mean Formula Sum Minimum Maximum Range Mode Median Variance Value of X j that has the largest observed frequency. If there are several modes, the first one encountered in the data is selected. The median is the 50th percentile. See Percentile, which is shown below. Standard Deviation Standard rror Percentile Survey Reporter uses one method for computation of percentiles. Let where p is the requested percentile divided by 100, and k 1 and k 2 satisfy Then

458 444 Chapter 19 Let x be the pth percentile; the definition is as follows: Formulae for Statistical Tests This section contains the formulae for the statistical tests available with IBM SPSS Data CollectionSurveyReporter. Statistical Formula for the Chi-Square Test The following table shows the notation used in this topic. Notation Description Observed frequency in row i, column j. Thisvalue is weighted in a weighted table, unweighted in an unweighted table. Number of rows contributing to the test. Number of columns contributing to the test. The total in row i: The total in column j:

459 445 Reference Notation Description The total in the table or section of the table being tested: The expected value in the table or section of the table being tested: where, for Pearson s formula: and for the Yates correction: The degrees of freedom are: For details of Fisher s exact test, see Appendix 5, p , SPSS 7.5 Statistical Algorithms (1997), Chicago, IL: SPSS Inc. ISBN Statistical Formula for the Column Proportions Test The column proportions test is performed separately for each relevant pair of columns within each relevant row and so the formula is presented in terms of one row and one pair of columns. The following table shows the notation used in this topic. Notation Description Weighted base in column i. Sum of squared weights for column i.

460 446 Chapter 19 Notation Description Weighted count in this row for column i. Weighted base for the overlap. Sum of squared weights for the overlap. Count in this row for the overlap. The proportion in each column i is Iftheeffectivebaseisbeingused,the effective base in each column i is Otherwise The test is not performed if: w i <= 0 The effective base is being used and q i <= 0 The proportions in the two columns being tested are identical The combined proportion for a pair of columns, 1 and 2, is The covariance term, v, and the effective base, e o, are both set to 0 if: Thedataarenotoverlapping The data are overlapping and w o <= 0 The data are overlapping and the effective base is being used and q o <= 0 Otherwise Figure 19-1

461 447 Reference Figure 19-2 Figure 19-3 xcept for grids, Z always reduces to the value of 1.0. For grids, the formula for Z is: Figure 19-4 Where r 0 = the count for this row in the overlap r 1 = the count for this row in column 1 for respondents in both columns r 2 = the count for this row in column 2 for respondents in both columns and w 0 is the base in the overlap, that is, the number of respondents who were asked both columns. The t value is calculated as Figure 19-5 where, The degrees of freedom, DF, are DF = e 1 + e 2 - e 0-2 The absolute value of t together with the degrees of freedom are used to calculate the probability, p, forthet value. If p is less than the significance level requested, the proportions in the two columns are deemed to be significantly different.

462 448 Chapter 19 Note: The grid overlap formula is applied when the columns have respondents in common, but some (or all) appear in different rows. The grid table normally complies with the rule that there is at least a multiple response categorical variable, or a grid or loop iterator, on both the side and the top. Statistical Formula for the Column Means Test The column means test is performed separately for each relevant pair of columns within a row that contains mean values and so the formula is presented in terms of one row and one pair of columns. The following table shows the notation used in this topic. Notation Description Weighted count of cases contributing to the mean in column i. Sum of squared weights for column i. Weighted count of cases contributing to the mean for the overlap. Sum of squared weights for the overlap. Weighted sum of the values in column i. Weighted sum of the squared values in column i. The mean in each column i is If the effective base is being used, the effective base in each column i is Otherwise The test is not performed if: w i <= 0 The effective base is being used and q i <= 0 Themeanvaluesinthetwocolumnsbeingtestedareidentical The sample variance in column i is

463 449 Reference If we set Then the pooled estimate of the population variance is The t value is With no overlap, Z and e o are both zero. With overlap, Z is 1.0, except in the case of grids, where it is: Figure 19-6 where: X 12 is the weighted sum, for respondents in both columns, of the value in column 1 multiplied by the value in column 2 all X and Y terms in Z refer to respondents who are in both columns. The degrees of freedom, DF, are DF = e 1 + e 2 - e 0-2 Note: The grid overlap formula is applied when the columns have respondents in common, but some (or all) appear in different rows. The grid table normally complies with the rule that there is at least a multiple response categorical variable, or a grid or loop iterator, on both the side and the top.

464 450 Chapter 19 Statistical Formula for the Least Significant Difference Test The formula for the least significant difference value for independent values is as follows: Notation Description Weighted count of cases contributing to the mean in column i. Weighted sum of the values in column i. Weighted sum of the squared values in column i. NCOL The number of columns in the group. The degrees of freedom are: Figure 19-7 degrees of freedom and the LSD value is: Figure 19-8 lsd formula where MS is the mean square: Figure 19-9 HM is the harmonic mean: Figure and SIGVAL is the critical value of T for DOF degrees of freedom at the significance level definedbytheuser.

465 451 Reference Statistical Formula for the Net Difference Test The following table shows the formulae used for conducting the net difference test in IBM SPSS Data Collection Survey Reporter. Formula for Proportions For any row, and any of the four columns being tested (i=1,2,3, and 4): Notation Description W i Sum of the weights (weighted base) for column i. Q i Sum of the squared weights for column i. i =(W i * W i )/Q i ffective base for column i. P i Proportion in column i For a table with overlap or a grid table, and any pair of columns from the four being tested (i and j=1,2,3, and 4): Notation W ij Q ij ij =(W ij * W ij )/Q ij P ij Description Sum of the weights (weighted base) for respondents in both columns. Sum of the squared weights for respondents in both columns. ffective base for respondents in both columns. Proportion for respondents belonging in the row being tested for both columns. The formula is: Figure where numer =(P 3 - P 4 )-(P 1 - P 2 ) and for a non-grid, non-overlap table Figure For a table with overlap or a grid table

466 452 Chapter 19 Figure where Figure The degrees of freedom are: Figure where, for a non-grid, non-overlap table Figure and Figure For a table with overlap or a grid table Figure and Figure 19-19

467 453 Reference Formula for Means For any row, and any of the four columns being tested (i=1,2,3, and 4): Notation Description W i Sum of the weights (weighted base) for column i. Q i Sum of the squared weights for column i. i =(W i * W i )/Q i ffective base for column i. X i sum of values for column i Y i sum of squared values for column i M i mean for column i=x i /W i The values may be either numeric values or factor values. For a table with overlap or a grid table, and any pair of columns from the four being tested (i and j=1,2,3, and 4): Notation W ij Q ij ij =(W ij * W ij )/Q ij Description Sum of the weights (weighted base) for respondents in both columns. Sum of the squared weights for respondents in both columns. ffective base for respondents in both columns. The intermediate term SX is: Figure The tstat is Figure where numer =(M 3 - M 4 )-(M 1 - M 2 ) and for a grid, non-overlap table,

468 454 Chapter 19 Figure For a table with overlap or a grid table Figure where Figure For a non-grid table with overlap, R ij reduces to 1. Grid tables For a grid table, it is not possible to display the net difference if the mean is a numeric mean rather than a factor mean. In this case, an error is returned. For a grid table with factor means: Notation X i* X *j Y i* Y *j Y ij Description The weighted sum of factors for column i for all respondents belonging in the mean for column i and in the base of column j. The weighted sum of factors for column j for all respondents belonging in the mean for column j and in the base of column i. The weighted sum of squared factors for column i for all respondents belonging in the mean for column i and in the base of column j The weighted sum of squared factors for column j for all respondents belonging in the mean for column j and in the base of column i The weighted sum of (factor for column i) * (factor for column j) for all respondents belonging in the mean for both columns. Using the above terms

469 455 Reference Figure where Figure Degrees of freedom The degrees of freedom are: Figure where, for a non-grid, non-overlap table: Figure and Figure For a table with overlap or a grid table: Figure and

470 456 Chapter 19 Figure For more on the theory of overlapping samples, see Kish, L (1965), Survey Sampling, NewYork: John Wiley and Sons. ISBN X. Statistical Formula for the Paired Preference Test The paired preference element is usually specified as a row element to compare two rows for each column independently. However, you can specify it as a column element to compare two columns for each row independently. The following information assumes specification as a row. The following table shows the formulae used for conducting the paired preference test in IBM SPSS Data Collection Survey Reporter. Notation w o w 2 o e o =(w o ) 2 / w 2 o c i c j p i = c i /w o p j = c j /w o Description Sum of the weights for the column. Sum of the squared weights for the column. ffective base for the column. Sum of the weights for the cell in the i th row. Sum of the weights for the cell in the j th row. Column proportion in the i th row. Column proportion in the j th row. Test Statistic Under the null hypothesis H o : p i = p j the paired preference test statistic is calculated using the following expression: The test is undefined if p i = p j =0orife o <2. Pvalues p values are computed using the t distribution with e o -1 degrees of freedom. References Kish, L (1965), Survey Sampling, New York: John Wiley and Sons. ISBN X.

471 457 Reference Statistical Tests Compared to IBM SPSS Statistics The formulae for the statistical tests in IBM SPSS Data Collection Survey Reporter have been specifically developed for the market research industry. The tests differ from the corresponding tests offered in IBM SPSS Statistics 10 in two main ways: Overlapping data. Survey Reporter allows you to run the column proportions and column means tests on overlapping data. When Survey Reporter detects overlapping data in the columns being tested, it automatically uses a special formula to compensate, known as the overlap adjustment. Weighted data. The statistical formulae in SPSS Statistics 10 are designed for data weighted with replication weights, which are normally integer values, whereas the statistical formulae in Survey Reporter are designed for data weighted with sample weights, which are normally non-integer values. Statistical Tests Compared to IBM SPSS Quantum and IBM SPSS Quanvert During the development of IBM SPSS Data Collection Survey Reporter, the algorithms for statistical formulae were rewritten, and the revised formulae were reviewed by IBM Corp. statisticians. Although the formulae appear very different to those used in IBM SPSS Quantum and IBM SPSS Quanvert, tests have shown that they give comparable p values. This section provides a comparison of the formulae in Survey Reporter and Quantum/Quanvert. Column Proportions Test In the column proportions test, where the data are not overlapping, the denominator of t = sqrt(term), where term is in Survey Reporter: in Quantum/Quanvert: Where there is overlap, the denominator of t =sqrt(term), where term is in Survey Reporter: in Quantum/Quanvert:

472 458 Chapter 19 In some cases, slight differences will be seen in your results as borderline cases that are significant using the Survey Reporter formula may not be significant using the Quantum/Quanvert formula. Degrees of freedom: in Survey Reporter: DF = e 1 + e 2 - e 0-2 in Quantum/Quanvert: DF = e 1 + e 2 - e 0-1 Customers who want to reproduce the Quantum/Quanvert formula can do this using the Use Quantum/Quanvert column proportions formula option available from the popup box in the Statistics tab of the Table Properties dialog box. For full detailsofthe SurveyReporter formula, seestatistical Formula for the Column Proportions Test. Column Means Test Degrees of freedom: in Survey Reporter: DF = e 1 + e 2 - e 0-2 in Quantum/Quanvert: DF = e 1 + e 2 - e 0-1 Customers who want to reproduce the Quantum/Quanvert formula can do this using the Use Quantum/Quanvert column proportions formula option available from the popup box in the Statistics tab of the Table Properties dialog box. For full details of the Survey Reporter formula, see Statistical Formula for the Column Means Test. Paired Preference Test In the paired preference test, the denominator of t =sqrt(term), where term is in Survey Reporter:

473 459 Reference in Quantum/Quanvert: where For full details of the Survey Reporter formula, see Statistical Formula for the Paired Preference Test. For full details of Quantum and Quanvert formulae, see the Quantum User s Guideor the Quanvert User s Guide. References Kish, L. Survey Sampling. New York: John Wiley and Sons. ISBN X.

474 Troubleshooting, Tips and Hints Chapter 20 This section contains answers to frequently asked questions and information that may help you resolve problems that you come across when using IBM SPSS Data Collection Survey Reporter. Frequently Asked Questions This topic provides answers to some frequently asked questions about working with IBM SPSS Data Collection Survey Reporter. Q. How can I search for specific text in a variable or category? A. Press Ctrl+F to open the Find dialog box, and enter the text you want to search for. For more information, see the topic Finding Tables or Variables in Chapter 3 on p. 39. Q. Can I sort variables? A. Yes. You can sort variables in the list view of the Variables pane. To display the list view, choose View > Variable List from the menu or press Alt+2. For more information, see the topic Sorting Variables in Chapter 3 on p. 46. Q. My results show a lot of empty rows and columns. How do I display tables without these? A. By default, all rows and columns are displayed. To hide empty rows and columns: PressF4toopentheTablePropertiesdialogbox. ChoosetheHidetab. Select the Hide rows and Hide columns check boxes. By default, this hides rows or columns where the value is zero. Choose OK. For more information, see the topic Hiding a Row or Column in Chapter 15 on p Q. Can I copy and paste a chart directly into another application without needing to export it? A. Yes. Right-click on the chart and choose Copy from the context menu. This copies the chart to the Windows clipboard and you can then paste it into another application. Q. When I change a variable, the changes apply to all tables where that variable is used. How do I change a variable on just one table? Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

475 461 Troubleshooting, Tips and Hints A. When you select a variable in the Variables pane and use the dit Variable menu option, the changes apply to the variable wherever it is used. If you want the changes to apply to a single table, first add the variable to the table, then select the variable on the table in the Design pane and use the dit Table Variable option on the Variables menu to edit it. For more information, see the topic diting variables in Chapter 7 on p Q. I want to create a table using a variable that contains verbatims, but I get an error message when I try to do this. Is it possible to tabulate this type of variable? A. You can tabulate text variables, and any other variables for which you want to see individual responses rather than aggregated data, using a profile table. To create a new profile table, choose Tables > New > Profile from the menu, or press Ctrl+R. For more information, see the topic Creating a Profile Table in Chapter 14 on p Q. Can I copy from one table to another? A. Yes. You can either copy the table syntax or you can copy the entire table. Copying an entire table copies all the information for the table, including any table properties or filters that you have set up. For more information, see the topic Copying a table in Chapter 4 on p. 71. Copying the table syntax copies just the structure (the variables on the top and side of the table). For more information, see the topic Copying table syntax in Chapter 4 on p. 78. IBM SPSS Data Collection Survey Reporter in Other Languages You can display the application in a language other than nglish. You can change the language at any time by following the appropriate instructions below for your computer s operating system. Close the application before making these changes. You can change the language back to nglish at any time or even switch back and forward between various languages. To Display the application in a Different Language On a Windows XP Professional or Windows Server computer: 1. Refer to the Microsoft article Set up Windows XP for multiple languages ( 2. Delete all files (for example, Default_DockingLayout.xml and Options.xml) from the following folders: For IBM SPSS Data Collection Author: C:\Documents and Settings\<Windows user name>\application Data\SPSSInc\IBM\SPSS\DataCollection\6\Author\ For IBM SPSS Data Collection Survey Reporter: C:\Documents and Settings\<Windows user name>\application DataSPSSInc\IBM\SPSS\DataCollection\6\Survey Reporter\

476 462 Chapter Modify the appropriate application configuration file to include the desired culture value. For example, add the following to change the language to French: <appsettings> <add key="culture" value="fr-fr" /> </appsettings> Language Chinese nglish French German Italian Japanese Spanish Culture Value ZH-cn en-us, or blank fr-fr de-d it-it ja-jp es-s For Author: [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\\Author\Author.exe.config For Survey Reporter: [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\\Survey Reporter\Reporter.exe.config For IBM SPSS Data Collection Base Professional: [INSTALL_FOLDR]\IBM\SPSS\DataCollection\6\Base Professional\mrstudio.exe.config On a Windows Vista Ultimate dition computer: 1. In the Windows Control Panel, open Regional and Language Options. 2. Click the Keyboard and Languages tab. In Display languages, click Install/uninstall languages 3. Click How can I install additional languages? for information on installing additional languages (for example Japanese or Simplified Chinese) in Windows Vista. 4. Follow the instructions for installing other display languages. 5. Follow the above steps 2 and 3 in On a Windows XP Professional or Windows Server computer. Troubleshooting Displaying Text in Other Languages Q. I have a survey that contains translations of the category descriptions, but the text appears in nglish in IBM SPSS Data Collection Survey Reporter. How do I display the translated text? A. To display the text in another language, you need to select the appropriate language from the list available in the File Properties dialog box. For more information, see the topic Changing the variable description language in Chapter 7 on p Q. I have a file containing Japanese text, but the characters are not recognized when I open the file in Survey Reporter. How can I display the text in Japanese?

477 463 Troubleshooting, Tips and Hints A. For languages that use Japanese or other Asian character sets, you must first install Asian language support on your computer. To do this: From the Windows Start menu, choose Settings > Control Panel > Regional Options (or Regional and Language Options on some machines). In Language Settings, select Install files for ast Asian Languages (you may need access to the installation disk to do this) and choose OK. You may need to reboot your computer when the installation is complete. Displaying Charts Q. I have installed Microsoft Office Web Components (OWC) but when I generate results I still see tables. How do I get charts? A. If you already have OWC when you install Survey Reporter, charts are enabled automatically. However, if you install OWC after Survey Reporter, you will not see any charts until you specifically enable them. To enable charts: From the Survey Reporter menu, choose Tools > Options In the Display tab, choose an option that includes charts from the Generate drop-down list (Table and Chart, Chart and Table, or Chart Only). xporting results Q. I do not have the option to export data when viewing a file on the server. What should I do? A. When using the Survey Reporter desktop interface, you cannot export data from a file on the server. To export data from a file on the server, access the file from the Web interface. Q. When I attempt to export my results to Microsoft Word or Microsoft xcel, I get a message about a security setting. What should I do? A. The Microsoft Word and Microsoft xcel exports use a Visual Basic for Applications (VBA) macro. The macro is temporarily inserted into the template and removed at the end of the export process. This requires a security setting to be set. For information on how to change this setting, see nabling security access for Microsoft xcel, Word, and PowerPoint exports. Q. When I attempt to export my results to Microsoft xcel, the export fails with the message Run-time error What should I do? A. Install the latest Microsoft Office service pack. To check the software you have installed and upgrade if necessary, choose the Check for Updates option on the Microsoft xcel Help menu to display the Microsoft Office Downloads page, where you can download the latest service pack.

478 464 Chapter 20 Using Samples Q. When I try to work with the samples provided with the IBM SPSS Data Collection Developer Library (DDL), the files are read-only. How can I make them writeable? A. On Windows Vista, the sample files provided with the DDL may be treated as read-only. To remove the read-only flag, you can copy the files to a location such as your desktop. Unweighted Data Q. I cannot use various options related to unweighted data when working with a file on the server. What should I do? A. Contact your administrator. You may not have the appropriate access to work with unweighted data. Access settings apply to all files on the server, regardless of whether you are working with them through the Web or desktop interface of Survey Reporter. For more information, see the topic Viewing Unweighted Data in Chapter 12 on p Q. I cannot connect to IBM SPSS Data Collection Survey Reporter Server dition when using a fully qualified machine name A. When a fully qualified machine name is used to access Survey Reporter Server dition or IBM SPSS Data Collection Author Server dition on an IBM SPSS Data Collection Interviewer Server the Survey Reporter Server dition/author Server ditionstarturl will need tobechanged(viadpm)tothefullyqualified machine name in order to prevent connection issues. Do not use a relative URL when updating the StartURL value. Q. I cannot connect to the database when attempting to access database questions? A. A Failure to connect to Database error may occur when attempting to work with database questions in Survey Reporter Server dition. This typically occurs when the running user (specified during installation) is a local user, but the database questions are defined with a trusted connection string. This scenario will result in a failure to connect to the selected database server. There are two solutions for this issue: Provide the running user access to the database. Assign the proper access permissions to the running user in the database server security settings. Change the running user to an authorized user in the IIS Directory Security setting. 1. Start IIS Manager on the database server and navigate to Default Web Site > SPSSMR > TabulationWebService. 2. Select the Directory Security tab and click dit in the Authentication and access control section. 3. Change the running user to a database server authorized user. Q. Why are the keyboard shortcuts not working in when the application is run in a Citrix environment?

479 465 Troubleshooting, Tips and Hints A. When running the application in a Citrix environment, the keyboard shortcuts/hot keys that are defined for the application may conflict with the default Citrix keyboard shortcuts. You can resolve the conflict by changing the conflicting Citrix keyboard shortcuts/hot keys. Refer to the following Citrix Knowledge Center article for more information: How to nable or Disable Hotkeys within an ICA file (including Template.ica) (

480 Accessibility Guide Chapter 21 This section provides an overview of alternative methods for accessing the functionality of the product. More specifically, the following topics are covered: Keyboard navigation of the software Special issues for visually impaired users Special issues for blind users Special considerations Important: If using a screen reader, use the F6 key to switch between this help system s Navigation pane and Contents pane. Keyboard Navigation Much of the product s functionality is accessible via the keyboard. At its most basic level, you can press the Alt key to activate window menus or press the Tab key to scroll through dialog box controls. For complete details about keyboard shortcuts in the IBM SPSS Data Collection Survey Reporter user interface, see the following topics: The IBM SPSS Data Collection Survey Reporter Menus The IBM SPSS Data Collection Survey Reporter Toolbar Buttons Accessibility for the Visually Impaired Youcanspecifyanumberofoptionstoenhance your ability to use the software: Use the Size and Layout tab of the Options dialog box to increase the font size of menu and toolbar text. For more information, see the topic Options: Size and Layout Tab in Chapter 18 on p Use the Size and Layout tab of the Options dialog box to increase the size of menu and toolbar icons. For more information, see the topic Options: Size and Layout Tab in Chapter 18 on p Use the Size and Layout tab of the Options dialog box to enable the ability to reposition and resize various window panes. For more information, see the topic Changing the Layout of the IBM SPSS Data Collection Survey Reporter Window in Chapter 3 on p. 37. Use the Results Display Options Dialog Box to change results to display in black and white or anumberofotherpredefined formats. Use the zoom drop-down on the toolbar to increase or decrease the display size of the Results tab. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

481 467 Accessibility Guide For more information, see the topic Special Considerations on p Accessibility for Blind Users Support for blind users is predominately dependent on the use of a screen reader. IBM SPSS Data Collection Survey Reporter has been tested with JAWS for Windows (copyright Freedom Scientific, For more information, see the topic Special Considerations: Interference with Other Software on p During testing with JAWS, it was found that listening to the table results is easier while in full screen view. To enter full screen view, press the F11 key. To exit full screen view, press the sc key. Important: If using a screen reader, use the F6 key to switch between this help system s Navigation pane and Contents pane. Special Considerations There are issues that deserve special attention, as outlined in the following topics. Note: Although we are working to make IBM SPSS Data Collection Survey Reporter accessible to all assistive technologies, Survey Reporter has been tested only with the JAWS for Windows screen reader software version 8.0. Special Considerations: Dialog Boxes The initial focus in a dialog box is generally placed on the control in the upper left area. From there, you can access other controls in the dialog box by pressing the Tab key. Alternatively, you can use the dialog box keyboard shortcuts listed below. The placement of a control in the tabbing order is determined by the section it belongs to, the type of control it is, and its placement in the dialog box. Note that some dialog boxes may not have all types of controls or the same number of controls. For dialog boxes containing more than one user interface tab (the Options dialog box, for example), the initial focus is generally placed on the first tab itself. Use the key combination Ctrl+Tab to navigate to other tabs. Press the Tab key to navigate through the controls on each tab. Special Considerations: Interference with Other Software When testing IBM SPSS Data Collection Survey Reporter with screen readers such as JAWS, other software may interfere. For example, our development team discovered that the use of a Systems Management Server (SMS) within your organization may interfere with JAWS ability

482 468 Chapter 21 to read some products. Disabling SMS will rectify this situation. Visit the Microsoft web site for more information about SMS.

483 Glossary Band. Group the responses to numeric questions into categories. For example, a numeric variable may store each respondent s exact age, but you may want to create a table showing age groups. You can achieve this by grouping the values into bands that represent the required age groups. Base. The total number of cases that are eligible for inclusion in a variable, a row, a column, or a table. The base is used in statistical tests and for calculating percentages. Block. Groups one or more questions into a block. Boolean variable. A special type of integer variable that can contain values of True or False. Also called a Yes/No variable. Case. The basic unit of analysis. In a data set based on a simple survey, a case generally corresponds to a respondent. However, in a hierarchical data set, what a case represents depends on the level. For example, in a household survey, respondents might be asked questions about their household, about each person in the household, and about each vehicle that belongs to the household. At the top level a case will therefore represent a household, at the person level, a case will represent a person, and at the vehicle level it will represent a vehicle. Cases correspond to records in the s virtual tables. Case data. The data recorded for each case. In a questionnaire or survey the case data stores the answers given by each respondent. CDSC. A component used to expose the case data in the underlying data store. Compound. Group for presentation purposes a number of related questions that share a category list. A compound is not the same as a grid, although a compound may contain one or more grids. Context. Defines the environment in which a text is to be used. You can keep several variations of each text in the metadata for use in different circumstances, as definedbythecontext for example, analysis, interviewing, and publishing. Data Collection Developer Library (DDL). A free, downloadable resource that provides information for scriptwriters developing automated survey and market research processes, software developers wanting to leverage products and technology, and those who simply want to understand more about the technology. The can also be installed from every product installation CD. Date variable. A variable that stores date and time information. Down-leving. The repetition of data from a higher level so that it can be represented at a child level. xpanded loop. When you are using a hierarchical view of the data, all loops are represented hierarchically as levels. However, when a loop is defined as expanded, it can also be viewed in an expanded (flattened) format as well, which means that you use it to create grid tables and you can select individual slices of the loop. Filter. Provides a way of restricting the cases that are included in a table. The filter defines a characteristic, or a set of characteristics, that the cases must have to be included; for example, respondents who were interviewed when they were leaving the museum. Full name. Constructed from the name of the item and the names of any items in which it is nested, the full name is useful in indicating where an item fits in a hierarchy. For example, if a variable is nested within a loop, the variable s full name will include the name of the loop. Brackets ([ ]) are used to indicate the iterations of a loop or grid and a single period (.) is used to indicate a parent/child relationship. Licensed Materials - Property of IBM Copyright IBM Corporation 2000,

484 470 Glossary Grid. A special type of loop in which all of the iterations are presented simultaneously to the respondent in a grid format. Grid questions often ask respondents to choose a rating on a predefined scale for a number of products in a list. Grid or loop slice. A single iteration of a grid or loop is sometimes called a slice. Label type. nable different types of labels to be created for different types of information. For example, the default label type of Label is used for question and category texts and variable descriptions, and the Instruction label type is used for interviewer instructions. Level. A tier in a hierarchical data structure. For example, a household survey might ask respondents to enter information about their household (type of accommodation, region, postal code, etc.), about each person in the household (age, gender, occupation, etc.), and about each overseas trip (if any) taken by each person in the household in the previous year (destination, mode of transport, etc.). When the response data is organized hierarchically, there would be three levels, with the topmost level storing the responses to the household questions, the next level storing the responses to the person questions, and the lowest level storing the responses to the trip questions. The lower levels (person and trip in this example) are represented as loops or grids in the metadata and as hierarchical tables in the Case Data Model. The level of a variable therefore indicates the variable s position in the overall hierarchy and the nature of the data it stores (whether it relates to a household, a person, or a trip). Loop. Aloopdefines a set of questions that are to be asked more than once. In a categorical loop, the number of times the loop is to be iterated (and therefore the number of times that the set of questions in the loop are to be asked) is controlled by the categories in a category list. For example, the set of questions can be asked for each product in a product list. In a numeric loop, the number of times the loop is to be iterated is controlled by a numeric expression. Maximum. The largest value. MDSC. A component used to expose the metadata in the underlying data store. Mean. A measure of central tendency. It is the arithmetic average; the sum divided by the number of cases. Median. The value above and below which half the cases fall; the 50th percentile. If there is an even number of cases, the median is the average of the two middle cases when they are sorted in ascending or descending order. The median is a measure of central tendency not sensitive to outlying values unlike the mean, which can be affected by one or more extremely high or low values. Metadata. Describes case data and typically includes such things as question texts, category names, translations, versions, and contexts. In the end-user documentation, the metadata is sometimes referred to as the questionnaire definition. Minimum. The smallest value. Mode. The most frequently occurring value. If several values share the greatest frequency of occurrence, each of them is a mode. Multiple response variable. A categorical variable that can have more than one value for each case for example, a variable based on a question to which the respondent can choose several answers from a predefined set of answers. A typical example is the question "What do you remember seeing in the museum today?" in response to which the respondent can select any number of items in a list. Also known as multiple categorical. Numeric variable. A variable that stores a numeric value for each case. A numeric variable can store an integer or a real value.

485 471 Glossary Percentile. A value that divides cases according to values below which certain percentages fall. For example, the 25th percentile is the value below which 25% of cases fall. Profiling. The display of non-aggregated respondent data, that is, a list of the responses given to questions by individual respondents. Range. The difference between the largest and smallest values the maximum minus the minimum. Single response variable. A categorical variable that can have only one value for each case, such as a variable based on a question that requires the respondent to choose one answer from a predefined set of answers. An example is the question "Have you visited this museum before?" to which the respondent must answer "Yes" or "No". Also known as single categorical. Standard deviation. A measure of dispersion around the mean. In a normal distribution, 68% of cases fall within one standard deviation of the mean and 95% of cases fall within two standard deviations. For example, if the mean age is 45 with a standard deviation of 10, then 95% of the cases would be between 25 and 65 in a normal distribution. Standard error. A measure of how much the value of the mean may vary from sample to sample takenfromthesamedistribution.thestandarderrorofthesamplemeancanbeusedtoestimatea mean value for the population as a whole. In a normal distribution, 95% of the values of the mean should lie in the range of plus and minus two times the standard error from the mean. Additionally, the standard error can be used to roughly compare the observed mean to a hypothesized value of another mean (that is, you can conclude the two values are different if the ratio of the difference to the standard error is less than -2 or greater than +2). Sum. The sum or total of the values. Superversion. A combination of two or more versions of the metadata. The versions are combined to form a superset, although when there is a conflict between, for example, a text in one or more of the versions, the more recent versions generally take precedence over the older versions. However, you can sometimes specify the order of precedence. You typically use a superversion when you want to export or analyze response data that has been collected using more than one version of the questionnaire. System variables. Standard variables that are present in most data sets to store standard information, such as the respondent s serial number, the mode of data collection used, the version of the questionnaire used to collect the data, etc. Some data sets (such as databases) do not have system variables. Text variable. A variable that contains data that is text, such as names and addresses or responses to open-ended questions. Unbounded loop. A loop in which the maximum number of times the loop may be iterated is unknown. This means that there is no upper limit to the number of times the questions in the loop can be asked. An unbounded loop cannot be defined as an expanded loop and therefore you cannot create grid tables from an unbounded loop. Up-leving. The collapsing of data from a lower level so that it can be represented at a parent level. Variance. This is the sample variance, which is a measure of dispersion around the mean, equal to the sum of squared deviations from the mean divided by one less than the number of cases. The sample variance is measured in units that are the square of those of the variable itself.

486 472 Glossary Weighting. Weighting is another term for sample balancing. You use weighting when you want the figures in your table to reflect your target population more accurately than the actual figures do. For example, suppose your target population consists of 57% women and 43% men, but you interviewed 50% women and 50% men for your survey. By applying weighting, you can make the women s figures count for more than the men s figures, so that they more accurately reflect the gender distribution in the target population. Weighting variable. A special numeric variable that has been set up to weight the data. You use weighting when you want the figures in your table to reflect your target population more accurately than the actual figures do. For example, suppose your target population consists of 57% women and 43% men, but you interviewed 50% women and 50% men for your survey. By applying weighting, you can make the women s figures count for more than the men s figures, so that they more accurately reflect the gender distribution in the target population. Well-formed HTML. Well-formed HTML (sometimes called XHTML) is HTML that conforms to the rules of XML. The same HTML tags are available, but stricter rules apply most notably, all tags must be closed and the same case must be used for opening and closing tags.

487 Index Access levels in IBM SPSS Data Collection Survey Reporter, 291 Accessibility, 466 blind users, 467 JAWS, 467 keyboard navigation, 466 screen reader, 467 special considerations, 467 visually impaired users, 466 Add cell contents, 81 Add Difference Attributes dialog box, 245 Add Factors dialog box, 169 Advanced dialog box, 31 Annotations changing annotations used in Word table of contents, 382 Array database variables icon, 113 Assets Publish utility, 421 Autobase calculation, 182 hiding, 186 overview, 182 Bands creating, 134, 168 Banners creating multiple tables using, 60 Bases built-in, 184 calculation, 182 diagnostics file, effective, 189, excluding from tables, 185 grid tables, 279 hiding, 186 in tables, 182 weighted, 261 Blocks icon, 113 overview, 124 Boolean variables icon, 113 overview, 124 Breakdowns creating multiple tables using, 60 bulk update table definitions, 75 table filters, 97 Cancel, 40 Categorical questions example, 116 Categorical variables adding categories, 135 deleting categories, 148 hiding categories, 149 icons, 113 inserting derived categories, 137 inserting summary statistics, 139 introduction, 116 overview, 116 removing categories, 144 Categories base, 182 changing descriptions, 127 changing language, 128 changing order, 128 collapsing into a combined category, 129 creating user-defined category, 135 deleting, 148 hiding, 149 net and keep, 130 nets, 130 removing, 144 updating counts, 141 categorization, categorize, 176 Category Selection dialog box, 99 Cell chi-square test diagnostics information, 248 Cell contents, 81, 331 about, 80 counts, 81 expected values, 90 indices, 87 percentages, 83 residuals, 90 rounding, 440 statistical formulae, 441 summary statistics of numeric variables, Cells hiding, 309, 311 Charts, , 325 custom charts, 376 setting chart types per table, 351 troubleshooting, 463 Chi-square test details and restrictions, 197 diagnostics information, 247 example, 194 overview, 194 requesting, 191 statistical formula, 198, 444 Citrix hot keys, 464 keyboard shortcuts, 464 Coding example, 119 Coding variables icon,

488 474 Index overview, 119 Column means test details and restrictions, 215 diagnostics information, 250 example, 210 least significant difference value, 209, 214, 219, 450 overview, 209 requesting, 191 statistical formula, 217, 448 Column percentages about, 83 Column proportions test details and restrictions, 205 diagnostics information, 249 example, 200 overview, 199 requesting, 191 statistical formula, 207, 445 Columns hiding, sorting, 298, 301 Combine combining categories, 129 in grid variables, 132 Compounds icon, 113 overview, 124 Concatenated tables sorting, 302 Contexts Variable description context option, 412 Copy table, 71, 78 table script, 72 Counts about, 81 expected values and residuals, 90 Create bands, 134, 168 filter, 17, 92 folders, 43, 46 grid table, 63 multiple tables, 60 Profile tables, 296 table, 13, 59, 61, 65, 67, 69 template document, Create New Variable Based On dialog box, 174 Crosstabulations concatenated, 302 creating, 13 nested, 302 CSS use in HTML table export component, 406 Cumulative percentages, 83 Custom charts, 376 Cut table, 71, 78 Data changing between hierarchical and flat view, 265 hierarchical, 264 Data files opening, 27 Data properties, 411 Data view, 412 database categorization, 179 database questions, 178 Date variables icon, 113 Decimal places counts, 81 expected values and residuals, 90 indices, 87 percentages, 83 rounding, 440 summary statistics of numeric variables, 87 Degrees of freedom cell chi-square test, 248 chi-square test, 194, 247 column means test, 250 column proportions test, 249 paired preference test, 251 T-test test, 239 Delete category, 148 filter, 94 table, 72 Derived category inserting in categorical variable, 137 derived variables, 178 Descriptions changing for categories, 127 changing for variable, 127 using HTML tags to format, 377 Diagnostics information statistical tests, 193, 246 Dialog boxes, 31 32, 39, 41, 43, 49, 67, 99, , , , , 176, 245, 331, 411, 413 Dictionary file, 467 Display options, 414 Distributing results, 394 Documentation about, 50 Double variables overview, 118 Down-leving filters, 283 dit filter, 93 dit Derived Category dialog box, 167 dit Table Variable dialog box, 172 dit User-Defined Item dialog box, 166 dit Variable dialog box, 156

489 475 Index ffective base diagnostics file, overview, selecting, 189 lements base, 185 sorting special elements, 306 valuatemptyiterations, 280 xcel exporting results to Microsoft xcel, 363 exporting tables to Microsoft xcel, 356 formatting the output, 374 xclude from base, 185 xit, 27 xpanded loops grid tables, 276 icon, 113 overview, 120 slices, 281 viewinginthevariables pane, 265 xpected values cell contents, 90 chi-square test, 197 T-test test, 240 xport data, 390 xporting results, , , 363, 366, 369, 372 tables to Microsoft Word, xcel, and PowerPoint, 356 xports troubleshooting, 463 File Locations options, 417 File properties, 412 File Properties dialog box, 411 Files opening, 27 opening and saving, 29 Filter variables overview, 124 Filters, And operator, 108 complex filters, 109 creating, 17, 92 defining conditions, deleting, 94 editing, 93 exporting filtered data, 394 hierarchical data, 283 introduction, 92 NOT operator, 108 Or operator, 108 saving, 95 setting levels, 97 valid names, 432 Find, 39 tables, 42 variables, 45 Fisher s exact test example, 195 overview, 194 Flat view changing to, 265 Folders creating, 43, 46 Footers defining, 313 exporting to Microsoft Word, 380 Format options, 417 Full labels, 281 Full names introduction, 265 overview, 120 Full-screen mode, 39 General file properties, 411 General options, 413 Generate variable preview, 49 Generate detailed statistical output, 412 Get values from data, 168 Getting started, 5 Global filters, 100 Global headers and footers, 319 overview, 313 Graphic, 396 Graphics displaying in category descriptions, 377 grid base, 280 grid iterations setting up bases, 280 Grid questions See Grids, 120 Grid tables sorting, 307 the base in, 279 understanding, 276 Grid variables creating tables using, 63 See grids, 120 Grids, 264 adding average, 140 combining categories, 132 creating summarized version, 133 icon, 113 overview, 120 slices, 281 summarized, 133 viewing in the Variables pane, 265 HDATA statistical tests, 257 Headers defining, 313

490 476 Index exporting to Microsoft Word, 380 Headers and footers, 319 adding notes, 315 Helper variables introduction, 116 Hide bases, 186 category, 149 panes and toolbars, 37 variables, 47 Hiding cells, 311 rows, columns, 310 rows, columns, cells, 309 Hierarchical data changing the view, 265 filters, 283 grid and loop slices, 281 grid tables, 276, 279 introduction, 120 sample data, 286 statistical tests, 257 understanding table generation levels, 267 working with, 264 Hierarchical view changing to, 265 working with, 264 hot keys Citrix, 464 Household sample overview, 286 usingtounderstand grid tables, 276, 279 using to understand table generation levels, 267 viewing in the Variables pane, 265 HTML customizing the style sheet, 406 using the formatted labels option, 377 IBM SPSS Data Collection Base Professional, 30, 395 IBM SPSS Data Collection Developer Library, 50 IBM SPSS Data Collection global filters, 101 IBM SPSS Data Collection Survey Reporter displaying a different language, 461 localization, 461 starting and exiting, 27 what s new, 2 IBM SPSS Data Collection Survey Reporter Professional, 279 IBM SPSS Data Collection Survey Tabulation, 30, 395 IBM SPSS Quanvert Table Specification (.qsf) files convertingtodatacollection Table document (.mtd) files, 398 IBM SPSS Statistics rounding, 440 statistical tests compared to, 457 Icons, 35, 41, 113 Images displaying in category descriptions, 377 Include at least/most filters, 109 include edited variables, 72 Include exactly filters, 109 Indices, 87 Insert Bands dialog box, 168 Insert Categories dialog box, 162 Interview filters, 101 Introduction installing, 1 Iterations overview, 120 tabulating, 281 viewing in the Variables pane, 265 JAWS, 467 Keyboard navigation, 466 keyboard shortcuts Citrix, 464 Keyboard shortcuts, 32, 35 in online help, 56 Labels changing for variable, 127 using HTML tags to format, 377 Landscape changing format for Microsoft Word export, 381 language changing, 461 Language changing language of variables, 128 Languages exporting, 391 troubleshooting, 462 Variable description language option, 412 Layout changing the window layout, 37 Least significant difference, 209, 214, 219, 450 Level of significance See significance level, 189 Levels filters, 283 grid and loop slices, 281 grid tables, 276, 279 introduction, 120 setting levels in filters, 97 understanding table generation levels, 267 Localization IBM SPSS Data Collection Survey Reporter, 461 Log files, 412

491 477 Index Logo, 396 displaying in category descriptions, 377 Long variables overview, 118 Loops icon, 113 overview, 120 slices, 281 viewing in the Variables pane, 265 working with data collected using, 264 Mapped category values overview, 116 Marginals, 141 Maximum number of responses, 170 Maximum value cell contents, 87.mdd files opening, 27 Mean adding to categorical variable, 139 adding to grid, 140 appears to be incorrect, 88 calculation of base, 182 cell contents, 87 creating mean summary tables, 65 creating summary means tables, 69 examples, 88 Mean summary tables, 65 Median, 87 Menu options, 32 Menus, 32 Microsoft xcel exporting results to Microsoft xcel, 363 exporting tables to Microsoft xcel, 356 formatting the output, 374 Microsoft PowerPoint exporting results to Microsoft PowerPoint, 366 exporting tables to Microsoft PowerPoint, 356 Microsoft Word exporting results to Microsoft Word, 369 exporting tables to Microsoft Word, 356 Microsoft Word tables export formatting, 380 styles, 384, 386, 389 templates, Minimum value cell contents, 87 Mode, 87 Modify Table Statistics dialog box opening, 191 overview, 190 Move tables, 43 toolbars and panes, 37 variables, 46.mtd files opening, 27 opening and saving, 29 multi-wave studies, 439 Multiple database variables icon, 113 Multiple response questions example, 116 overview, 116 Multiple response variables icon, 113 introduction, 116 statistical tests, 256 multiwave studies, 439 Namespaces shorten long variable names, 414 Nested tables sorting, 302 Nesting variables, 61 net and keep, 130 Net difference test details and restrictions, 222 diagnostics information, 250 example, 221 overview, 220 statistical formula, 223, 451 Nets how to create, 130 sorting, 305 New Variable dialog box, 173 Notes adding to headers and footers, 315 null grid base, 280 Null hypothesis, 252 Number of Responses dialog box, 170 Numeric variable unable to add, 119 Numeric variables icon, 113 overview, 118 summarizing, 138 summary statistics as cell contents, Online Help about, 50 navigating, 50 navigating using the keyboard, 56 printing information from, 53 searching for information in, 51 using the toolbar, 54 Open files from IBM SPSS Data Collection Interviewer Server Administration, 291 survey data files, 5, 27 table document files, 29

492 478 Index Open from IBM SPSS Data Collection Interviewer Server Administration survey data files, 27 Open From IBM SPSS Data Collection Interviewer Server Administration table document files, 29 Open from server survey data files, 27 table document files, 29 Open-ended questions coding, 119 overview, 119 Options dialog box, 413 Other Specify category example, 116 Other Specify variables introduction, 116 Overlap adjustment, 256 Overlapping data, 256 pvalues cell chi-square test, 248 chi-square test, 194, 247 column means test, 250 column proportions test, 249 overview, 252 paired preference test, 251 T-test test, 239 Paired preference test details and restrictions, 233 diagnostics information, 251 xample, 229 overview, 228 requesting, 192 statistical formula, 233, 456 Panes moving and resizing, 37 Paste table, 71, 78 Percentages about, 83 Percentiles, 87 PowerPoint exporting results to Microsoft PowerPoint, 366 exporting tables to Microsoft PowerPoint, 356 Preview table printout, 354 variable printout, 48 variables, 49 Print tables, 354 variables, 48 Product difference test, overview, 234 Profile data option to keep when saving, 412 Profiles, 296 creating, 296 saving, 297 Projects changing between hierarchical and flat view, 265 Properties pane, dit Variable dialog box, 157 Publishing results, , , 363, 366, 369, 372 QSF converting to Data Collection Table document (.mtd) files, 398 QSF to MTD conversion, 398 Ranges, 87 Redo, 40 Remove category, 144 cell contents, 81 template document, 402 Rename tables, 42, 45 Residuals, 90 Resize toolbars and panes, 37 Results exporting, , 357 exporting to HTML, 358 exporting to Microsoft xcel, 363 exporting to Microsoft PowerPoint, 366 exporting to Microsoft Word, 369 exporting to text file, 372 saving, 29 Rounding about, 440 Row percentages about, 83 Rows hiding, sorting, 298, 301 Sample data household, 286 Sample variance cell contents, 87 Samples troubleshooting, 464 Save filter, 95 Profile tables, 297 table document, 11 table document files, 29 Save Variable As dialog box, 162 Screen readers, 467 Script pane, dit Variable dialog box, 161

493 479 Index Search, 39 for tables, 42 for variables, 45 Security settings for exporting tables, 356 Select columns to display, 340 Server files working with, 291 setting up bases grid iterations, 280 Significance level defining for a statistical test, 189 observed, 252 Simple Categorization dialog box, 176 Simple database variables icon, 113 Single response questions example, 116 overview, 116 Single response variables icon, 113 introduction, 116 Size and Layout options, 417 Slices introduction, 120 overview, 281 viewing in the Variables pane, 265 Snapshots, 141 Sort variables, 46 Sorting grid tables, 307 nested and concatenated tables, 302 nets, 305 rows and columns, 298, 301 special elements, 306 Standard deviation cell contents, 87 Standard error cell contents, 87 column means test, 250 column proportions test, 249 paired preference test, 251 Start, 27 statistical formulae for cell contents, 441 Statistical formulae paired preference test, 233, 456 Statistical tests, 188, , 246, 338, 340 adding and removing tests, 190 chi-square test, 194 column means test, 209 column proportions test, 199 compared to IBM SPSS Statistics, 457 diagnostics, 193, 246 effective base, 189, Fisher s exact test, hierarchical data, 257 Net difference test, overlapping data, 256 p values, 252 paired preference test, , 233, 456 product difference test, 234, specifying, T-test test, 239 Style sheet customizing for HTML tables export, 406 Styles exporting tables to HTML, 406 Microsoft Word, 384, 386, 389 using when exporting tables to Microsoft xcel, 374 using when exporting tables to Microsoft Word, 380 Subheadings adding to table, 142 summarized grids, 133 summarized version in grid variables, 133 Summarizing numeric variables step-by-step instructions, 138 Summary means creating tables of, 65 summary means tables, 69 Summary Statistic Table dialog box, 67 Summary statistics creating tables of, 65 inserting in categorical variable, 139 Sums cell contents, 87 expected values and residuals, 90 Survey data open files, 5 opening, 27 Switch top and side of a table, 60 Syntax, 422 System variables icon, 113 T-test test details and restrictions, 240 example, 239 overview, 239 statistical formula, 240 table definitions bulk update, 75 Table display properties, 335 Table document save, 11 Table documents, 395 creating, 31 opening, 29 table filters bulk update, 97

494 480 Index Table filters, 99 Table properties dialog box, 331 Table specification syntax, 422 Tables bases, 182 copying and pasting, 71, 78 copying script, 72 creating, 13, 59, 65, 67, 69 creating grid tables, 63 creating multiple tables with same top, 60 creating nested tables, 61 creating profile tables, 296 deleting, 72 exporting, , 357 exporting to HTML, 358 exporting to Microsoft xcel, 363 exporting to Microsoft PowerPoint, 366 exporting to Microsoft Word, 369 exporting to Microsoft Word, xcel, and PowerPoint, 356 exporting to text file, 372 filtering when using hierarchical data, 283 finding tables, 42 grid, 276, 279 grid and loop slices, 281 hiding cells, 311 hiding rows, columns, 310 hiding rows, columns, cells, 309 include edited variables, 72 moving, 43 printing, 354 profile tables, 296 renaming, 42, 45 rounding of cell contents, 440 saving profile tables, 297 sorting rows and columns, 298, 301 switching top and side, 60 understanding generation levels, 267 weighting, 260 working with hierarchical data, 264 Tables pane, 41 Template documents creating, removing, 402 Templates, 399 bookmarks, 383 Microsoft Word, Text adding to table, 142 usinghtmltagstoformat, 377 Text file exporting results to text file, 372 Text variables icon, 113 overview, 119 Texts changing for categories, 127 changing for variable, 127 Toolbars, 35 moving and resizing, 37 Top2box,170 creating, 132 Top two box, 170 creating, 132 Top two ratings creating, 132 Total percentages, 83 tracking studies sort options for reusable tables, 298 Transpose, 60 unable to add variable, 119 Undo, 40 Unweighted base, 261 Unweighted counts, 81 Unweighted data viewing, 293 Unweighted Data troubleshooting, 464 Up-leving filters, 283 User-defined categories adding to variable, 135 Variable Preview, 49 Variable preview cache location, 412 Variables adding categories, 135 adding derived categories, 137 adding summary statistics, 139 banding, 134 changing category descriptions, 127 changing descriptions, 127 changing language, 128 changing order of categories, 128 collapsing categories, 129 creating nets, 130 deleting categories, 148 exporting, 393 finding variables, 45 hiding, 47 hiding categories, 149 icons, 113 moving, 46 overview, 113 printing, 48 removing categories, 144 sorting, 46 summarizing numeric, 138 updating counts, 141 valid names, 432 Variables Folders pane, 43 Variables pane hierarchical data, 265

495 481 Index Variance, 87 Versions, 294 wave studies sort options for reusable tables, 298 Weighting, 337 compared to IBM SPSS Statistics, 457 statistical tests, summary statistics of numeric variables, 87 tables, 260 unweighted base, 261 viewing unweighted data, 293 Weighting variables icon, 113 What s new IBM SPSS Data Collection Survey Reporter, 2 Windows, 32 Word exporting results to Microsoft Word, 369 exporting tables to Microsoft Word, 356 Word tables export defining the positions of the tables etc., 383 formatting, 380 styles, 384, 386, 389 templates, XML CDSC changing the view, 265