Chapter Eight: Quantitative Methods



Similar documents
Descriptive Statistics

Research Methods & Experimental Design

Overview of Non-Parametric Statistics PRESENTER: ELAINE EISENBEISZ OWNER AND PRINCIPAL, OMEGA STATISTICS

DATA ANALYSIS. QEM Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University

Data Analysis, Research Study Design and the IRB

Guided Reading 9 th Edition. informed consent, protection from harm, deception, confidentiality, and anonymity.

SPSS Tests for Versions 9 to 13

SPSS ADVANCED ANALYSIS WENDIANN SETHI SPRING 2011

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance

Quantitative Research: Reliability and Validity

Inferential Statistics. What are they? When would you use them?

Pre-experimental Designs for Description. Y520 Strategies for Educational Inquiry

DATA COLLECTION AND ANALYSIS

SCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES

STATISTICAL ANALYSIS WITH EXCEL COURSE OUTLINE

UNDERSTANDING ANALYSIS OF COVARIANCE (ANCOVA)

Experimental Design and Hypothesis Testing. Rick Balkin, Ph.D.

Projects Involving Statistics (& SPSS)

Sampling. COUN 695 Experimental Design

Data Definitions Adapted from the Glossary How to Design and Evaluate Research in Education by Jack R. Fraenkel and Norman E.

Reporting Statistics in Psychology

MTH 140 Statistics Videos

Study Guide for the Final Exam

II. DISTRIBUTIONS distribution normal distribution. standard scores

WHAT IS A JOURNAL CLUB?

January 26, 2009 The Faculty Center for Teaching and Learning

Appendix B Checklist for the Empirical Cycle

Statistics Review PSY379

Essentials of Marketing Research

When to Use a Particular Statistical Test

Nursing Journal Toolkit: Critiquing a Quantitative Research Article

Data analysis process

Moore, D., & McCabe, D. (1993). Introduction to the practice of statistics. New York: Freeman.

Data Analysis in SPSS. February 21, If you wish to cite the contents of this document, the APA reference for them would be

Working with data: Data analyses April 8, 2014

Additional sources Compilation of sources:

Directions for using SPSS

In an experimental study there are two types of variables: Independent variable (I will abbreviate this as the IV)

HYPOTHESIS TESTING: CONFIDENCE INTERVALS, T-TESTS, ANOVAS, AND REGRESSION

Intro to Parametric & Nonparametric Statistics

UNIVERSITY OF NAIROBI

Data Mining Techniques Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools

research/scientific includes the following: statistical hypotheses: you have a null and alternative you accept one and reject the other

Elements of statistics (MATH0487-1)

Descriptive Methods Ch. 6 and 7

Consider a study in which. How many subjects? The importance of sample size calculations. An insignificant effect: two possibilities.

Marketing Research Core Body Knowledge (MRCBOK ) Learning Objectives

Rank-Based Non-Parametric Tests

Chapter 13 Introduction to Linear Regression and Correlation Analysis

Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics

MASTER COURSE SYLLABUS-PROTOTYPE PSYCHOLOGY 2317 STATISTICAL METHODS FOR THE BEHAVIORAL SCIENCES

EXCEL Analysis TookPak [Statistical Analysis] 1. First of all, check to make sure that the Analysis ToolPak is installed. Here is how you do it:

10. Analysis of Longitudinal Studies Repeat-measures analysis

Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.

DESCRIPTIVE RESEARCH DESIGNS

Homework 11. Part 1. Name: Score: / null

Introduction to Quantitative Methods

Fairfield Public Schools

Biostatistics: Types of Data Analysis

Evaluation: Designs and Approaches

Experimental methods. Elisabeth Ahlsén Linguistic Methods Course

Description. Textbook. Grading. Objective

NORTHERN VIRGINIA COMMUNITY COLLEGE PSYCHOLOGY RESEARCH METHODOLOGY FOR THE BEHAVIORAL SCIENCES Dr. Rosalyn M.

An analysis method for a quantitative outcome and two categorical explanatory variables.

Silvermine House Steenberg Office Park, Tokai 7945 Cape Town, South Africa Telephone:

SPSS Explore procedure

IBM SPSS Statistics 20 Part 4: Chi-Square and ANOVA

12/30/2012. Research Design. Quantitative Research: Types (Campbell & Stanley, 1963; Crowl, 1993)

This chapter provides information on the research methods of this thesis. The

Outline. Definitions Descriptive vs. Inferential Statistics The t-test - One-sample t-test

RESEARCH DESIGN PART 2. Experimental Research Design. Purpose

STATISTICS FOR PSYCHOLOGISTS

Simple Linear Regression Inference

Developing an implementation research proposal. Session 2: Research design

Introduction to Regression and Data Analysis

Examining Differences (Comparing Groups) using SPSS Inferential statistics (Part I) Dwayne Devonish


Post-hoc comparisons & two-way analysis of variance. Two-way ANOVA, II. Post-hoc testing for main effects. Post-hoc testing 9.

Cleveland State University NAL/PAD/PDD/UST 504 Section 51 Levin College of Urban Affairs Fall, 2009 W 6 to 9:50 pm UR 108

Statistical Models in R

business statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar

2 Precision-based sample size calculations

Introduction to Analysis of Variance (ANOVA) Limitations of the t-test

(and sex and drugs and rock 'n' roll) ANDY FIELD

The impact of Discussion Classes on ODL Learners in Basic Statistics Ms S Muchengetwa and Mr R Ssekuma muches@unisa.ac.za, ssekur@unisa.ac.

Types of Group Comparison Research. Stephen E. Brock, Ph.D., NCSP EDS 250. Causal-Comparative Research 1

Analysing Questionnaires using Minitab (for SPSS queries contact -)

Introduction to Statistics and Quantitative Research Methods

Mathematics within the Psychology Curriculum

COM 365: INTRODUCTION TO COMMUNICATION RESEARCH METHODS Unit Test 3 Study Guide

School of Mathematics and Science MATH 153 Introduction to Statistical Methods Section: WE1 & WE2

Analyzing Intervention Effects: Multilevel & Other Approaches. Simplest Intervention Design. Better Design: Have Pretest

Statistical Analysis RSCH 665 Eagle Vision Classroom - Blended Course Syllabus

IPDET Module 6: Descriptive, Normative, and Impact Evaluation Designs

Measuring Evaluation Results with Microsoft Excel

SAMPLING & INFERENTIAL STATISTICS. Sampling is necessary to make inferences about a population.

SPSS Guide How-to, Tips, Tricks & Statistical Techniques

Service courses for graduate students in degree programs other than the MS or PhD programs in Biostatistics.

Calculating Effect-Sizes

Transcription:

Chapter Eight: Quantitative Methods RESEARCH DESIGN Qualitative, Quantitative, and Mixed Methods Approaches Third Edition John W. Creswell

Chapter Outline Defining Surveys and Experiments Components of a Survey Method Plan The Survey Design The Population and Sample Instrumentation Variables in the Study Data Analysis and Interpretation Components of an Experimental Method Plan Participants Variables Instrumentation and Materials Experimental Procedures Threats to Validity The Procedure Data Analysis Interpreting Results

Defining Surveys Survey Design To provide a quantitative description of trends, attitudes, or opinions of a population Components of a Survey Method Plan The Survey Design The Population and Sample Instrumentation Variables in the Study Data Analysis and Interpretation

A Survey Method Plan The Survey Design Provide a rationale for using a survey Indicate the type of survey design: Cross-sectional (data collected at one point in time) Longitudinal (data collected over time) The Population and Sample Specify the characteristics of the population (size, sampling frame) Specify the sampling procedures Single stage or multi-stage Random or convenience Use a sample size formula to determine the needed sample size

A Survey Method Plan Instrumentation Provide detailed information about the survey instrument How developed, Pilot testing Sample items, Types of scores Describe the validity and reliability scores of past and/or current uses of the instrument Validity: whether one can draw meaning and useful inferences from scores on the instruments Reliability: whether scores resulting from past use are internally consistent, have high test-retest correlations, and result from consistent scoring Describe steps for administering survey and ensuring a high response rate

A Survey Method Plan Variables in the Study Relate the variables to research questions and items on the instrument Data Analysis and Interpretation Present the steps for analyzing the data Step 1. Report response rate Step 2. Determine response bias: the effect of nonresponses on survey estimates Step 3. Conduct descriptive analyses Step 4. Check instrument's scales Step 5. Conduct inferential statistical analyses (see Table 8.3) Step 6. Present and interpret results

Table 8.3 Criteria for Choosing Select Statistical Tests Nature of Question # of Independent Variables # of Dependent Variables # of Control Variables Type of Score Ind. / Dep. Variables Distribution of Scores Statistical Test Group comparison 1 1 0 Categorical / Continuous Normal t-test Group comparison 1 or more 1 0 Categorical / Continuous Normal Analysis of variance Group comparison 1 or more 1 1 Categorical / Continuous Normal Analysis of covariance Group comparison 1 1 0 Categorical / Continuous Non-normal Mann-Whitney U test Association between groups 1 1 0 Categorical / Categorical Non-normal Chi-square Relate variables 1 1 0 Continuous / Continuous Relate variables 2 or more 1 0 Continuous / Continuous Relate variables 1 1 or more 0 Categorical / Categorical Normal Normal Non-normal Pearson product moment correlation Multiple regression Spearman rankorder correlation

Defining Experiments Experimental Design To test the impact of a treatment on an outcome, controlling for other factors that might influence that outcome Components of an Experimental Method Plan Participants Variables Instrumentation and Materials Experimental Procedures Threats to Validity

An Experimental Method Plan Participants Describe the selection of participants Random or convenience Describe the assignment of participants to groups Random or not; Consider matching participants Describe the procedures for determining the number of participants per group Variables Clarify the groups Identify the independent variable(s), including the treatment variable Identify the dependent variable(s), the outcomes

An Experimental Method Plan Instrumentation and Materials Discuss instruments development, items, and scales reliability and validity reports of past uses Thoroughly discuss materials used for the treatment Experimental Procedures Identify the type of experiment Pre-experimental, true experiment, quasi-experiment, and singlesubject designs Identify the type of comparisons: within-group or between-subject Provide a visual model X = treatment O = observation

An Experimental Method Plan Consider Threats to Validity Threats to internal validity: procedures, treatments, or experiences of the participants that threaten the researcher's ability to draw conclusions about cause and effect Threats to external validity: characteristics of the sample, setting, or timing that threaten the researcher's ability to generalize the conclusions to a population Threats to statistical conclusion validity: inadequate statistical power or violation of statistical assumptions that threaten the researcher's ability to draw statistical inferences Threats to construct validity: inadequate definitions and measures of variables that threaten the researcher's ability to measure relevant constructs

Threats to Validity (Tables 8.5 & 8.6) Threats to Internal Validity History Maturation Regression Selection Mortality Diffusion of treatment Compensatory/resentful demoralization Compensatory rivalry Testing Instrumentation Threats to External Validity Interaction of selection and treatment Interaction of setting and treatment Interaction of history and treatment

An Experimental Method Plan The Procedure Describe in detail the procedure for conducting the experiment Procedures for pre-test post-test control group design Measure dependent variable as a pre-test Assign participants to matched pairs based on scores Randomly assign one member of each pair to the control and experimental group Expose experimental group to the treatment Measure dependent variable as a post-test from both groups Compare groups statistically

An Experimental Method Plan Data Analysis Report descriptive statistics (e.g., means, standard deviations, ranges) Conduct inferential statistical tests (e.g., t test, ANOVA, ANCOVA, or MANOVA) Use line graphs for single subject designs Report confidence intervals and effect sizes in addition to statistical tests Interpreting Results Discuss results, limitations, and implications

Chapter Eight: Quantitative Methods RESEARCH DESIGN Qualitative, Quantitative, and Mixed Methods Approaches Third Edition John W. Creswell