Factor Analysis and Structural equation modelling
|
|
|
- Darleen Davis
- 7 years ago
- Views:
Transcription
1 Factor Analysis and Structural equation modelling Herman Adèr Previously: Department Clinical Epidemiology and Biostatistics, VU University medical center, Amsterdam Stavanger July 4 13, 2006 Herman Adèr 1
2 Overview 1 E C 2 EFA 3 CFA 4 SEM Exploratory Confirmatory methods Exploratory Factor Analysis Confirmatory Factor Analysis Structural Equation Modelling Herman Adèr 2
3 Overview 1 E C 2 EFA 3 CFA 4 SEM Exploratory Confirmatory methods Exploratory Factor Analysis Confirmatory Factor Analysis Structural Equation Modelling Herman Adèr 2
4 Overview 1 E C 2 EFA 3 CFA 4 SEM Exploratory Confirmatory methods Exploratory Factor Analysis Confirmatory Factor Analysis Structural Equation Modelling Herman Adèr 2
5 Overview 1 E C 2 EFA 3 CFA 4 SEM Exploratory Confirmatory methods Exploratory Factor Analysis Confirmatory Factor Analysis Structural Equation Modelling Herman Adèr 2
6 Overview 1 E C 2 EFA 3 CFA 4 SEM Exploratory Confirmatory methods Exploratory Factor Analysis Confirmatory Factor Analysis Structural Equation Modelling Herman Adèr 2
7 Part VI Factor analysis and Herman Adèr Factor Analysis and SEM 3
8 Detective Judge Herman Adèr Factor Analysis and SEM 5
9 Characterization of Tukey (1977) Exploratory data analysis is detective in character. Confirmatory data analysis is judicial or quasi-judicial in character... Unless the detective finds the clues, judge or jury has nothing to consider. Unless exploratory data analysis uncovers indications, usually quantitative ones, there is likely to be nothing for confirmatory data analysis to consider. On the other hand: Exploratory data analysis can never be the whole story, but nothing else can serve as the foundation stone the first step. Herman Adèr Factor Analysis and SEM 7
10 Characterization of Tukey (1977) Exploratory data analysis is detective in character. Confirmatory data analysis is judicial or quasi-judicial in character... Unless the detective finds the clues, judge or jury has nothing to consider. Unless exploratory data analysis uncovers indications, usually quantitative ones, there is likely to be nothing for confirmatory data analysis to consider. On the other hand: Exploratory data analysis can never be the whole story, but nothing else can serve as the foundation stone the first step. Herman Adèr Factor Analysis and SEM 7
11 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure F = M U E, of which M indicate the meaningful factors, U so-called unique factors (factors on which only one item loads) and E error factors. Questions we try to settle using EFA 1 How many meaningful dimensions are present? 2 What is the structure of those dimensions? Herman Adèr Factor Analysis and SEM 8
12 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure F = M U E, of which M indicate the meaningful factors, U so-called unique factors (factors on which only one item loads) and E error factors. Questions we try to settle using EFA 1 How many meaningful dimensions are present? 2 What is the structure of those dimensions? Herman Adèr Factor Analysis and SEM 8
13 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Data set: { } D = Subject Items Exploratory Factor Analysis factor structure determine meaningful factors unrotated Three steps 1 Determine the meaningful factors rotate factor structure k meaningful factors 2 Rotate 3 Interpret the factor structure determine factor meaning final factor solution Herman Adèr Factor Analysis and SEM 9
14 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure determine meaningful factors: scree plot eigenvalues larger than 1 GoF change significant between solutions total variance explained more than 50% select factors with intelligible loading patterns and name them communalities reliabilities doubtful Herman Adèr Factor Analysis and SEM 10
15 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure CES-D: A multidimensional scale to assess Depression FACTOR /VARIABLES cesd1 cesd2 cesd3 cesd4 cesd5 cesd6 cesd7 cesd8 cesd9 cesd10 cesd11 cesd12 cesd13 cesd14 cesd15 cesd16 cesd17 cesd18 cesd19 cesd20 /MISSING LISTWISE /ANALYSIS cesd1 cesd2 cesd3 cesd4 cesd5 cesd6 cesd7 cesd8 cesd9 cesd10 cesd11 cesd12 cesd13 cesd14 cesd15 cesd16 cesd17 cesd18 cesd19 cesd20 /PRINT all /FORMAT BLANK(.30) /PLOT EIGEN /CRITERIA MINEIGEN(0) ITERATE(100) factors(3) /EXTRACTION pc /ROTATION norotate. Herman Adèr Factor Analysis and SEM 12
16 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure CES-D: A multidimensional scale to assess Depression FACTOR /VARIABLES cesd1 cesd2 cesd3 cesd4 cesd5 cesd6 cesd7 cesd8 cesd9 cesd10 cesd11 cesd12 cesd13 cesd14 cesd15 cesd16 cesd17 cesd18 cesd19 cesd20 /MISSING LISTWISE /ANALYSIS cesd1 cesd2 cesd3 cesd4 cesd5 cesd6 cesd7 cesd8 cesd9 cesd10 cesd11 cesd12 cesd13 cesd14 cesd15 cesd16 cesd17 cesd18 cesd19 cesd20 /PRINT all /FORMAT BLANK(.30) /PLOT EIGEN /CRITERIA MINEIGEN(0) ITERATE(100) factors(3) /EXTRACTION pc /ROTATION norotate. Herman Adèr Factor Analysis and SEM 12
17 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure 10 Scree Plot Eigenvalue Component Number Herman Adèr Factor Analysis and SEM 13
18 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Component Initial Eigenvalues Total % of Variance Cumulative % Extraction Method: Principal Component Analysis. Herman Adèr Factor Analysis and SEM 14
19 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Interpretation of the unrotated factor structure Component CESD CESD CESD CESD CESD CESD6 CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD Extraction Method: Principal Component Analysis. Herman Adèr Factor Analysis and SEM 15
20 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Communalities: four factors and all factors Communalities Initial Extraction CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD Extraction Method: Principal Component Analysis. Communalities Initial Extraction CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD Extraction Method: Principal Component Analysis. Herman Adèr Factor Analysis and SEM 16
21 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Communalities: two and three factors Communalities Initial Extraction CESD CESD E-02 CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD Extraction Method: Principal Component Analysis. Communalities Initial Extraction CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD CESD Extraction Method: Principal Component Analysis. Herman Adèr Factor Analysis and SEM 17
22 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Goodness-of-fit criterium # Facts GoF χ 2 Df χ 2 change Df χ 2 α= As one can see by comparing the 0.05 threshold χ 2 in the last column Herman Adèr Factor Analysis and SEM 18
23 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Unrotated Rotated Factor Factor Item I II III I II III CESD CESD CESD CESD04 + CESD CESD CESD CESD08 + CESD CESD CESD CESD12 + CESD CESD CESD CESD16 + CESD CESD CESD CESD Herman Adèr Factor Analysis and SEM 19
24 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Interpretation of table I Unrotated Rotated Factor Factor Item I II III I II III CESD CESD CESD CESD04 + CESD CESD CESD CESD08 + CESD CESD CESD CESD12 + CESD CESD CESD CESD16 + CESD CESD CESD CESD All items with high positive loadings on the unrotated Factor I still load on this factor after rotation, but some of them (5, 6, 7, 9, 17, 18 and 20) also load on factor II. This makes that Factor I is now separated into two sublists, of which the above could be called the pure depression scale while (1, 3, 10, 11, 13, 14, 15, 19) includes a sublist indicating less severe symptoms of depression. Herman Adèr Factor Analysis and SEM 20
25 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Interpretation of table II Unrotated Rotated Factor Factor Item I II III I II III CESD CESD CESD CESD04 + CESD CESD CESD CESD08 + CESD CESD CESD CESD12 + CESD CESD CESD CESD16 + CESD CESD CESD CESD Factor II now also contains all the items that loaded negatively on Factor I before (4, 8, 12 and 16). We called this a factor that measures: general attitude towards life. Herman Adèr Factor Analysis and SEM 21
26 Questions and answers Three steps Determining the meaningful factors Rotation Interpretation of the factor structure Interpretation of table III Unrotated Rotated Factor Factor Item I II III I II III CESD CESD CESD CESD04 + CESD CESD CESD CESD08 + CESD CESD CESD CESD12 + CESD CESD CESD CESD16 + CESD CESD CESD CESD After rotation, Factor III now contains only item 2 ( I did not feel like eating: my appetite was poor ) and item 11 ( My sleep was restless ), suggesting that it is a factor that has to do with physical aspects of depression. Herman Adèr Factor Analysis and SEM 22
27 Example of EQS input Example of EQS input Conclusions of EFA and CFA combined Example of EQS input /TITLE Cesd; /SPECIFICATIONS VARIABLES=6; CASES= 200; DATAFILE= cesd.ess ; MATRIX=RAW; ME = ML; /EQUATIONS V1 = 2 * F1 + E1; V2 = 2 * F1 + E2; V3 = 2 * F2 + E3; V4 = 2 * F2 + E4; V5 = 2 * F3 + E5; V6 = 2 * F3 + E6; F1 = 2 * F2 + 2*F3+ D1; /VARIANCES E1 to E10 = 0.2*; D1, D2, D3 = 0.2*; /COVARIANCES F2,F3 =.5*; /END Herman Adèr Factor Analysis and SEM 23
28 Example of EQS input Example of EQS input Conclusions of EFA and CFA combined CES-D: Conclusions of the CFA The varimax solution is not fully confirmed: item 5, 6, 7, 18 and 20 have negligible coefficients on the second factor. The assumption of a orthogonal factor structure is unfounded: The correlations between the factors are (F1, F2) = 0.241; (F1, F3) = and (F2, F3) = Herman Adèr Factor Analysis and SEM 24
29 Example of EQS input Example of EQS input Conclusions of EFA and CFA combined CES-D: Conclusions of the CFA The varimax solution is not fully confirmed: item 5, 6, 7, 18 and 20 have negligible coefficients on the second factor. The assumption of a orthogonal factor structure is unfounded: The correlations between the factors are (F1, F2) = 0.241; (F1, F3) = and (F2, F3) = Herman Adèr Factor Analysis and SEM 24
30 Example of EQS input Example of EQS input Conclusions of EFA and CFA combined Conclusions of EFA and CFA combined 1 The first factor is a general depression factor (item 1, 3, 5, 6, 7, 10, 13, 14, 15, 18, 19 and 20) 2 The second factor contains the positively formulated items (4, 8, 9, 12, 16, 17). It represents a general attitude towards life. 3 The third factor contains items that have to do with physical aspects of depression. Herman Adèr Factor Analysis and SEM 25
31 Example: Post-traumatic stress disorder Example of a postulated structure Draw pictures! Herman Adèr Factor Analysis and SEM 26
32 Example: Post-traumatic stress disorder Example of a postulated structure Draw pictures! Herman Adèr Factor Analysis and SEM 26
33 Example: Post-traumatic stress disorder Example of a postulated structure Draw pictures! Herman Adèr Factor Analysis and SEM 26
34 Postulated structure Structure found Herman Adèr Factor Analysis and SEM 27
35 Recommended literature Factor analysis: Friendly (1995) ( Principal component analysis: Jackson (1991) : Bollen (1989), Kaplan (2000) Herman Adèr Factor Analysis and SEM 28
36 Summary Herman Adèr Factor Analysis and SEM 29
37 Summary In factor analysis the contrast between exploratory and confirmatory approaches is quite clear: the available techniques are different although related. can well be performed with principal component analysis, possibly combined with Maximum likelihood factor analysis. PCA is first used to determine the meaningful factors, MLFA for the final factor structure. Structural Equation Modelling makes it possible to analyze a research problem that has been represented as a diagram. Herman Adèr Factor Analysis and SEM 30
38 Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley and Sons. Friendly, M. (1995). Annotated Factor Analysis Bibliography. Jackson, J. E. (1991). A user s guide to principal components. New York: Wiley. Kaplan, D. (2000). Structural Equation Modeling. Foundations and Extensions. Thousand Oaks London New Delhi: Sage Publications. Tukey, J. W. (1977). Exploratory data analysis. Reading, MA: Addison Wesley. Herman Adèr Factor Analysis and SEM 31
Overview of Factor Analysis
Overview of Factor Analysis Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 Phone: (205) 348-4431 Fax: (205) 348-8648 August 1,
Rachel J. Goldberg, Guideline Research/Atlanta, Inc., Duluth, GA
PROC FACTOR: How to Interpret the Output of a Real-World Example Rachel J. Goldberg, Guideline Research/Atlanta, Inc., Duluth, GA ABSTRACT THE METHOD This paper summarizes a real-world example of a factor
Factor Analysis. Principal components factor analysis. Use of extracted factors in multivariate dependency models
Factor Analysis Principal components factor analysis Use of extracted factors in multivariate dependency models 2 KEY CONCEPTS ***** Factor Analysis Interdependency technique Assumptions of factor analysis
A Brief Introduction to SPSS Factor Analysis
A Brief Introduction to SPSS Factor Analysis SPSS has a procedure that conducts exploratory factor analysis. Before launching into a step by step example of how to use this procedure, it is recommended
Chapter 7 Factor Analysis SPSS
Chapter 7 Factor Analysis SPSS Factor analysis attempts to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. Factor analysis is often
Factor Analysis. Advanced Financial Accounting II Åbo Akademi School of Business
Factor Analysis Advanced Financial Accounting II Åbo Akademi School of Business Factor analysis A statistical method used to describe variability among observed variables in terms of fewer unobserved variables
Common factor analysis
Common factor analysis This is what people generally mean when they say "factor analysis" This family of techniques uses an estimate of common variance among the original variables to generate the factor
T-test & factor analysis
Parametric tests T-test & factor analysis Better than non parametric tests Stringent assumptions More strings attached Assumes population distribution of sample is normal Major problem Alternatives Continue
Exploratory Factor Analysis
Exploratory Factor Analysis ( 探 索 的 因 子 分 析 ) Yasuyo Sawaki Waseda University JLTA2011 Workshop Momoyama Gakuin University October 28, 2011 1 Today s schedule Part 1: EFA basics Introduction to factor
Introduction to Principal Components and FactorAnalysis
Introduction to Principal Components and FactorAnalysis Multivariate Analysis often starts out with data involving a substantial number of correlated variables. Principal Component Analysis (PCA) is a
An introduction to. Principal Component Analysis & Factor Analysis. Using SPSS 19 and R (psych package) Robin Beaumont robin@organplayers.co.
An introduction to Principal Component Analysis & Factor Analysis Using SPSS 19 and R (psych package) Robin Beaumont robin@organplayers.co.uk Monday, 23 April 2012 Acknowledgment: The original version
Factor Analysis Using SPSS
Psychology 305 p. 1 Factor Analysis Using SPSS Overview For this computer assignment, you will conduct a series of principal factor analyses to examine the factor structure of a new instrument developed
Factor Analysis. Sample StatFolio: factor analysis.sgp
STATGRAPHICS Rev. 1/10/005 Factor Analysis Summary The Factor Analysis procedure is designed to extract m common factors from a set of p quantitative variables X. In many situations, a small number of
5.2 Customers Types for Grocery Shopping Scenario
------------------------------------------------------------------------------------------------------- CHAPTER 5: RESULTS AND ANALYSIS -------------------------------------------------------------------------------------------------------
To do a factor analysis, we need to select an extraction method and a rotation method. Hit the Extraction button to specify your extraction method.
Factor Analysis in SPSS To conduct a Factor Analysis, start from the Analyze menu. This procedure is intended to reduce the complexity in a set of data, so we choose Data Reduction from the menu. And the
FACTOR ANALYSIS. Factor Analysis is similar to PCA in that it is a technique for studying the interrelationships among variables.
FACTOR ANALYSIS Introduction Factor Analysis is similar to PCA in that it is a technique for studying the interrelationships among variables Both methods differ from regression in that they don t have
Exploratory Factor Analysis of Demographic Characteristics of Antenatal Clinic Attendees and their Association with HIV Risk
Doi:10.5901/mjss.2014.v5n20p303 Abstract Exploratory Factor Analysis of Demographic Characteristics of Antenatal Clinic Attendees and their Association with HIV Risk Wilbert Sibanda Philip D. Pretorius
CHAPTER 4 EXAMPLES: EXPLORATORY FACTOR ANALYSIS
Examples: Exploratory Factor Analysis CHAPTER 4 EXAMPLES: EXPLORATORY FACTOR ANALYSIS Exploratory factor analysis (EFA) is used to determine the number of continuous latent variables that are needed to
Factor Analysis Example: SAS program (in blue) and output (in black) interleaved with comments (in red)
Factor Analysis Example: SAS program (in blue) and output (in black) interleaved with comments (in red) The following DATA procedure is to read input data. This will create a SAS dataset named CORRMATR
Applications of Structural Equation Modeling in Social Sciences Research
American International Journal of Contemporary Research Vol. 4 No. 1; January 2014 Applications of Structural Equation Modeling in Social Sciences Research Jackson de Carvalho, PhD Assistant Professor
PRINCIPAL COMPONENT ANALYSIS
1 Chapter 1 PRINCIPAL COMPONENT ANALYSIS Introduction: The Basics of Principal Component Analysis........................... 2 A Variable Reduction Procedure.......................................... 2
Current Topics in Statistics for Applied Researchers Factor Analysis
Current Topics in Statistics for Applied Researchers Factor Analysis George J. Knafl, PhD Professor & Senior Scientist knaflg@ohsu.edu Purpose to describe and demonstrate factor analysis of survey instrument
Social Media Marketing Management 社 會 媒 體 行 銷 管 理 確 認 性 因 素 分 析. (Confirmatory Factor Analysis) 1002SMMM12 TLMXJ1A Tue 12,13,14 (19:20-22:10) D325
Social Media Marketing Management 社 會 媒 體 行 銷 管 理 確 認 性 因 素 分 析 (Confirmatory Factor Analysis) 1002SMMM12 TLMXJ1A Tue 12,13,14 (19:20-22:10) D325 Min-Yuh Day 戴 敏 育 Assistant Professor 專 任 助 理 教 授 Dept.
Research Methodology: Tools
MSc Business Administration Research Methodology: Tools Applied Data Analysis (with SPSS) Lecture 02: Item Analysis / Scale Analysis / Factor Analysis February 2014 Prof. Dr. Jürg Schwarz Lic. phil. Heidi
A Brief Introduction to Factor Analysis
1. Introduction A Brief Introduction to Factor Analysis Factor analysis attempts to represent a set of observed variables X 1, X 2. X n in terms of a number of 'common' factors plus a factor which is unique
Factor Analysis. Chapter 420. Introduction
Chapter 420 Introduction (FA) is an exploratory technique applied to a set of observed variables that seeks to find underlying factors (subsets of variables) from which the observed variables were generated.
The president of a Fortune 500 firm wants to measure the firm s image.
4. Factor Analysis A related method to the PCA is the Factor Analysis (FA) with the crucial difference that in FA a statistical model is constructed to explain the interrelations (correlations) between
Principal Component Analysis
Principal Component Analysis Principle Component Analysis: A statistical technique used to examine the interrelations among a set of variables in order to identify the underlying structure of those variables.
Exploratory Factor Analysis
Introduction Principal components: explain many variables using few new variables. Not many assumptions attached. Exploratory Factor Analysis Exploratory factor analysis: similar idea, but based on model.
Partial Least Squares (PLS) Regression.
Partial Least Squares (PLS) Regression. Hervé Abdi 1 The University of Texas at Dallas Introduction Pls regression is a recent technique that generalizes and combines features from principal component
Exploratory Factor Analysis and Principal Components. Pekka Malo & Anton Frantsev 30E00500 Quantitative Empirical Research Spring 2016
and Principal Components Pekka Malo & Anton Frantsev 30E00500 Quantitative Empirical Research Spring 2016 Agenda Brief History and Introductory Example Factor Model Factor Equation Estimation of Loadings
What is Rotating in Exploratory Factor Analysis?
A peer-reviewed electronic journal. Copyright is retained by the first or sole author, who grants right of first publication to the Practical Assessment, Research & Evaluation. Permission is granted to
Multivariate Analysis
Table Of Contents Multivariate Analysis... 1 Overview... 1 Principal Components... 2 Factor Analysis... 5 Cluster Observations... 12 Cluster Variables... 17 Cluster K-Means... 20 Discriminant Analysis...
Running head: ONLINE VALUE AND SELF-EFFICACY SCALE
Online Value and Self-Efficacy Scale Running head: ONLINE VALUE AND SELF-EFFICACY SCALE Development and Initial Validation of the Online Learning Value and Self-Efficacy Scale Anthony R. Artino Jr. and
Factor Analysis: Statnotes, from North Carolina State University, Public Administration Program. Factor Analysis
Factor Analysis Overview Factor analysis is used to uncover the latent structure (dimensions) of a set of variables. It reduces attribute space from a larger number of variables to a smaller number of
FACTOR ANALYSIS NASC
FACTOR ANALYSIS NASC Factor Analysis A data reduction technique designed to represent a wide range of attributes on a smaller number of dimensions. Aim is to identify groups of variables which are relatively
Using Principal Components Analysis in Program Evaluation: Some Practical Considerations
http://evaluation.wmich.edu/jmde/ Articles Using Principal Components Analysis in Program Evaluation: Some Practical Considerations J. Thomas Kellow Assistant Professor of Research and Statistics Mercer
4. There are no dependent variables specified... Instead, the model is: VAR 1. Or, in terms of basic measurement theory, we could model it as:
1 Neuendorf Factor Analysis Assumptions: 1. Metric (interval/ratio) data 2. Linearity (in the relationships among the variables--factors are linear constructions of the set of variables; the critical source
Exploratory Factor Analysis
Exploratory Factor Analysis Definition Exploratory factor analysis (EFA) is a procedure for learning the extent to which k observed variables might measure m abstract variables, wherein m is less than
Statistics in Psychosocial Research Lecture 8 Factor Analysis I. Lecturer: Elizabeth Garrett-Mayer
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this
Principal Component Analysis
Principal Component Analysis ERS70D George Fernandez INTRODUCTION Analysis of multivariate data plays a key role in data analysis. Multivariate data consists of many different attributes or variables recorded
Tjalling C. Koopmans Research Institute
Tjalling C. Koopmans Research Institute Tjalling C. Koopmans Research Institute Utrecht School of Economics Utrecht University Kriekenpitplein 21-22 3584 TC Utrecht The Netherlands telephone +31 30 253
O n g o i n g D i s c u s s i o n
O n g o i n g D i s c u s s i o n Université de Genève, Switzerland Abstract: Utilisation of structural equations with latent variables is one promising strategy for social representation theory development.
I n d i a n a U n i v e r s i t y U n i v e r s i t y I n f o r m a t i o n T e c h n o l o g y S e r v i c e s
I n d i a n a U n i v e r s i t y U n i v e r s i t y I n f o r m a t i o n T e c h n o l o g y S e r v i c e s Confirmatory Factor Analysis using Amos, LISREL, Mplus, SAS/STAT CALIS* Jeremy J. Albright
How To Run Factor Analysis
Getting Started in Factor Analysis (using Stata 10) (ver. 1.5) Oscar Torres-Reyna Data Consultant otorres@princeton.edu http://dss.princeton.edu/training/ Factor analysis is used mostly for data reduction
Exploratory Factor Analysis Brian Habing - University of South Carolina - October 15, 2003
Exploratory Factor Analysis Brian Habing - University of South Carolina - October 15, 2003 FA is not worth the time necessary to understand it and carry it out. -Hills, 1977 Factor analysis should not
Questionnaire Evaluation with Factor Analysis and Cronbach s Alpha An Example
Questionnaire Evaluation with Factor Analysis and Cronbach s Alpha An Example - Melanie Hof - 1. Introduction The pleasure writers experience in writing considerably influences their motivation and consequently
SPSS and AMOS. Miss Brenda Lee 2:00p.m. 6:00p.m. 24 th July, 2015 The Open University of Hong Kong
Seminar on Quantitative Data Analysis: SPSS and AMOS Miss Brenda Lee 2:00p.m. 6:00p.m. 24 th July, 2015 The Open University of Hong Kong SBAS (Hong Kong) Ltd. All Rights Reserved. 1 Agenda MANOVA, Repeated
Effectiveness of Performance Appraisal: Its Outcomes and Detriments in Pakistani Organizations
Effectiveness of Performance Appraisal: Its Outcomes and Detriments in Pakistani Organizations Hafiz Muhammad Ishaq Federal Urdu University of Arts, Science and Technology, Islamabad, Pakistan E-mail:
Structural Equation Modelling (SEM)
(SEM) Aims and Objectives By the end of this seminar you should: Have a working knowledge of the principles behind causality. Understand the basic steps to building a Model of the phenomenon of interest.
Data analysis process
Data analysis process Data collection and preparation Collect data Prepare codebook Set up structure of data Enter data Screen data for errors Exploration of data Descriptive Statistics Graphs Analysis
2. Linearity (in relationships among the variables--factors are linear constructions of the set of variables) F 2 X 4 U 4
1 Neuendorf Factor Analysis Assumptions: 1. Metric (interval/ratio) data. Linearity (in relationships among the variables--factors are linear constructions of the set of variables) 3. Univariate and multivariate
Topic 10: Factor Analysis
Topic 10: Factor Analysis Introduction Factor analysis is a statistical method used to describe variability among observed variables in terms of a potentially lower number of unobserved variables called
Factor Analysis. Factor Analysis
Factor Analysis Principal Components Analysis, e.g. of stock price movements, sometimes suggests that several variables may be responding to a small number of underlying forces. In the factor model, we
EXPLORATORY FACTOR ANALYSIS IN MPLUS, R AND SPSS. sigbert@wiwi.hu-berlin.de
EXPLORATORY FACTOR ANALYSIS IN MPLUS, R AND SPSS Sigbert Klinke 1,2 Andrija Mihoci 1,3 and Wolfgang Härdle 1,3 1 School of Business and Economics, Humboldt-Universität zu Berlin, Germany 2 Department of
Factor analysis. Angela Montanari
Factor analysis Angela Montanari 1 Introduction Factor analysis is a statistical model that allows to explain the correlations between a large number of observed correlated variables through a small number
Psychology 7291, Multivariate Analysis, Spring 2003. SAS PROC FACTOR: Suggestions on Use
: Suggestions on Use Background: Factor analysis requires several arbitrary decisions. The choices you make are the options that you must insert in the following SAS statements: PROC FACTOR METHOD=????
FEATURE. Abstract. Introduction. Background
FEATURE From Data to Information: Using Factor Analysis with Survey Data Ronald D. Fricker, Jr., Walter W. Kulzy, and Jeffrey A. Appleget, Naval Postgraduate School; rdfricker@nps.edu Abstract In irregular
Factor analysis and Concurrent Validity of a University Counseling Center Presenting Problems Checklist
A RESEARCH REPORT OF THE RESEARCH CONSORTIUM OF COUNSELING & PSYCHOLOGICAL SERVICES IN HIGHER EDUCATION Factor analysis and Concurrent Validity of a University Counseling Center Presenting Problems Checklist
What Are Principal Components Analysis and Exploratory Factor Analysis?
Statistics Corner Questions and answers about language testing statistics: Principal components analysis and exploratory factor analysis Definitions, differences, and choices James Dean Brown University
How to report the percentage of explained common variance in exploratory factor analysis
UNIVERSITAT ROVIRA I VIRGILI How to report the percentage of explained common variance in exploratory factor analysis Tarragona 2013 Please reference this document as: Lorenzo-Seva, U. (2013). How to report
Confirmatory factor analysis in MPlus
Jan Štochl, Ph.D. Department of Psychiatry University of Cambridge Email: js883@cam.ac.uk Confirmatory factor analysis in MPlus The Psychometrics Centre Agenda of day 1 General ideas and introduction to
The Effectiveness of Ethics Program among Malaysian Companies
2011 2 nd International Conference on Economics, Business and Management IPEDR vol.22 (2011) (2011) IACSIT Press, Singapore The Effectiveness of Ethics Program among Malaysian Companies Rabiatul Alawiyah
SPSS ADVANCED ANALYSIS WENDIANN SETHI SPRING 2011
SPSS ADVANCED ANALYSIS WENDIANN SETHI SPRING 2011 Statistical techniques to be covered Explore relationships among variables Correlation Regression/Multiple regression Logistic regression Factor analysis
Factor Analysis - 2 nd TUTORIAL
Factor Analysis - 2 nd TUTORIAL Subject marks File sub_marks.csv shows correlation coefficients between subject scores for a sample of 220 boys. sub_marks
Data Analysis in Mixed Research: A Primer
Data Analysis in Mixed Research: A Primer Anthony J. Onwuegbuzie (Corresponding author) & Julie P. Combs Department of Educational Leadership and Counseling Sam Houston State University, USA Box 2119,
RR765 Applied Multivariate Analysis
Semester: Fall 2007 RR765 Applied Multivariate Analysis Course Instructor: Dr. Jerry J. Vaske 491-2360 email: jerryv@cnr.colostate.edu Office: 244 Forestry Bldg. Office Hours: Tuesday/Thursdays 1:00 2:00
A Casual Structure Analysis of Smart phone Addiction: Use Motives of Smart phone Users and Psychological Characteristics
A Casual Structure Analysis of Smart phone Addiction: Use Motives of Smart phone Users and Psychological Characteristics Dept. of Social Welfare, BaekSeok Culture University, ijoo65@hanmail.net Abstract
Empirical Model-Building and Response Surfaces
Empirical Model-Building and Response Surfaces GEORGE E. P. BOX NORMAN R. DRAPER Technische Universitat Darmstadt FACHBEREICH INFORMATIK BIBLIOTHEK Invortar-Nf.-. Sachgsbiete: Standort: New York John Wiley
Part III. Item-Level Analysis
Part III Item-Level Analysis 6241-029-P3-006-2pass-r02.indd 169 1/16/2013 9:14:56 PM 6241-029-P3-006-2pass-r02.indd 170 1/16/2013 9:14:57 PM 6 Exploratory and Confirmatory Factor Analysis Rex Kline 6.1
Chapter VIII Customers Perception Regarding Health Insurance
Chapter VIII Customers Perception Regarding Health Insurance This chapter deals with the analysis of customers perception regarding health insurance and involves its examination at series of stages i.e.
Succession planning in Chinese family-owned businesses in Hong Kong: an exploratory study on critical success factors and successor selection criteria
Succession planning in Chinese family-owned businesses in Hong Kong: an exploratory study on critical success factors and successor selection criteria By Ling Ming Chan BEng (University of Newcastle upon
Factors affecting teaching and learning of computer disciplines at. Rajamangala University of Technology
December 2010, Volume 7, No.12 (Serial No.73) US-China Education Review, ISSN 1548-6613, USA Factors affecting teaching and learning of computer disciplines at Rajamangala University of Technology Rungaroon
Principle Component Analysis and Partial Least Squares: Two Dimension Reduction Techniques for Regression
Principle Component Analysis and Partial Least Squares: Two Dimension Reduction Techniques for Regression Saikat Maitra and Jun Yan Abstract: Dimension reduction is one of the major tasks for multivariate
PARTIAL LEAST SQUARES IS TO LISREL AS PRINCIPAL COMPONENTS ANALYSIS IS TO COMMON FACTOR ANALYSIS. Wynne W. Chin University of Calgary, CANADA
PARTIAL LEAST SQUARES IS TO LISREL AS PRINCIPAL COMPONENTS ANALYSIS IS TO COMMON FACTOR ANALYSIS. Wynne W. Chin University of Calgary, CANADA ABSTRACT The decision of whether to use PLS instead of a covariance
How To Understand Multivariate Models
Neil H. Timm Applied Multivariate Analysis With 42 Figures Springer Contents Preface Acknowledgments List of Tables List of Figures vii ix xix xxiii 1 Introduction 1 1.1 Overview 1 1.2 Multivariate Models
Introduction to Principal Component Analysis: Stock Market Values
Chapter 10 Introduction to Principal Component Analysis: Stock Market Values The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from
Psychology 405: Psychometric Theory Homework on Factor analysis and structural equation modeling
Psychology 405: Psychometric Theory Homework on Factor analysis and structural equation modeling William Revelle Department of Psychology Northwestern University Evanston, Illinois USA June, 2014 1 / 20
EM Clustering Approach for Multi-Dimensional Analysis of Big Data Set
EM Clustering Approach for Multi-Dimensional Analysis of Big Data Set Amhmed A. Bhih School of Electrical and Electronic Engineering Princy Johnson School of Electrical and Electronic Engineering Martin
Practical Considerations for Using Exploratory Factor Analysis in Educational Research
A peer-reviewed electronic journal. Copyright is retained by the first or sole author, who grants right of first publication to the Practical Assessment, Research & Evaluation. Permission is granted to
Review Jeopardy. Blue vs. Orange. Review Jeopardy
Review Jeopardy Blue vs. Orange Review Jeopardy Jeopardy Round Lectures 0-3 Jeopardy Round $200 How could I measure how far apart (i.e. how different) two observations, y 1 and y 2, are from each other?
Confidence Intervals for One Standard Deviation Using Standard Deviation
Chapter 640 Confidence Intervals for One Standard Deviation Using Standard Deviation Introduction This routine calculates the sample size necessary to achieve a specified interval width or distance from
Multivariate Analysis (Slides 13)
Multivariate Analysis (Slides 13) The final topic we consider is Factor Analysis. A Factor Analysis is a mathematical approach for attempting to explain the correlation between a large set of variables
APPRAISAL OF FINANCIAL AND ADMINISTRATIVE FUNCTIONING OF PUNJAB TECHNICAL UNIVERSITY
APPRAISAL OF FINANCIAL AND ADMINISTRATIVE FUNCTIONING OF PUNJAB TECHNICAL UNIVERSITY In the previous chapters the budgets of the university have been analyzed using various techniques to understand the
Missing Data: Part 1 What to Do? Carol B. Thompson Johns Hopkins Biostatistics Center SON Brown Bag 3/20/13
Missing Data: Part 1 What to Do? Carol B. Thompson Johns Hopkins Biostatistics Center SON Brown Bag 3/20/13 Overview Missingness and impact on statistical analysis Missing data assumptions/mechanisms Conventional
The Latent Variable Growth Model In Practice. Individual Development Over Time
The Latent Variable Growth Model In Practice 37 Individual Development Over Time y i = 1 i = 2 i = 3 t = 1 t = 2 t = 3 t = 4 ε 1 ε 2 ε 3 ε 4 y 1 y 2 y 3 y 4 x η 0 η 1 (1) y ti = η 0i + η 1i x t + ε ti
Best Practices in Exploratory Factor Analysis: Four Recommendations for Getting the Most From Your Analysis
A peer-reviewed electronic journal. Copyright is retained by the first or sole author, who grants right of first publication to the Practical Assessment, Research & Evaluation. Permission is granted to
This section of the memo will review the questions included in the UW-BHS survey that will be used to create a social class index.
Social Class Measure This memo discusses the creation of a social class measure. Social class of the family of origin is one of the central concepts in social stratification research: students from more
The Effect of Macroeconomic Factors on Indian Stock Market Performance: A Factor Analysis Approach
IOSR Journal of Economics and Finance (IOSR-JEF) e-issn: 2321-5933, p-issn: 2321-5925. Volume 1, Issue 3 (Sep. Oct. 2013), PP 14-21 The Effect of Macroeconomic Factors on Indian Stock Market Performance:
Repairing Tom Swift s Electric Factor Analysis Machine
UNDERSTANDING STATISTICS, 2(1), 13 43 Copyright 2003, Lawrence Erlbaum Associates, Inc. TEACHING ARTICLES Repairing Tom Swift s Electric Factor Analysis Machine Kristopher J. Preacher and Robert C. MacCallum
DIGITAL CITIZENSHIP. TOJET: The Turkish Online Journal of Educational Technology January 2014, volume 13 issue 1
DIGITAL CITIZENSHIP Aytekin ISMAN a *, Ozlem CANAN GUNGOREN b a Sakarya University, Faculty of Education 54300, Sakarya, Turkey b Sakarya University, Faculty of Education 54300, Sakarya, Turkey ABSTRACT
Factor Rotations in Factor Analyses.
Factor Rotations in Factor Analyses. Hervé Abdi 1 The University of Texas at Dallas Introduction The different methods of factor analysis first extract a set a factors from a data set. These factors are
Analyzing Structural Equation Models With Missing Data
Analyzing Structural Equation Models With Missing Data Craig Enders* Arizona State University cenders@asu.edu based on Enders, C. K. (006). Analyzing structural equation models with missing data. In G.
A Beginner s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis
Tutorials in Quantitative Methods for Psychology 2013, Vol. 9(2), p. 79-94. A Beginner s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis An Gie Yong and Sean Pearce University of Ottawa
Introduction to Matrix Algebra
Psychology 7291: Multivariate Statistics (Carey) 8/27/98 Matrix Algebra - 1 Introduction to Matrix Algebra Definitions: A matrix is a collection of numbers ordered by rows and columns. It is customary
A REVIEW OF SCALE DEVELOPMENT PRACTICES IN NONPROFIT MANAGEMENT AND MARKETING
Walter Wymer, Helena Maria Baptista Alves 143 Walter Wymer, Helena Maria Baptista Alves, A Review of Scale Development Practices in Nonprofit Management and Marketing, Economics & Sociology, Vol. 5, No
Moderation. Moderation
Stats - Moderation Moderation A moderator is a variable that specifies conditions under which a given predictor is related to an outcome. The moderator explains when a DV and IV are related. Moderation
Presentation Outline. Structural Equation Modeling (SEM) for Dummies. What Is Structural Equation Modeling?
Structural Equation Modeling (SEM) for Dummies Joseph J. Sudano, Jr., PhD Center for Health Care Research and Policy Case Western Reserve University at The MetroHealth System Presentation Outline Conceptual
Exploratory Factor Analysis: rotation. Psychology 588: Covariance structure and factor models
Exploratory Factor Analysis: rotation Psychology 588: Covariance structure and factor models Rotational indeterminacy Given an initial (orthogonal) solution (i.e., Φ = I), there exist infinite pairs of
Exploratory data analysis for microarray data
Eploratory data analysis for microarray data Anja von Heydebreck Ma Planck Institute for Molecular Genetics, Dept. Computational Molecular Biology, Berlin, Germany heydebre@molgen.mpg.de Visualization