A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling
A Step-by-Step Approach to Using the SAS System for
Factor Analysis and Structural Equation Modeling
Larry Hatcher, Ph.D.
Acknowledgements
Dedication
Using This Book
Chapter 1 Principal Component Analysis
- Introduction: The Basics of Principal Component Analysis
- Example: Analysis of the Prosocial Orientation Inventory
- SAS Program and Output
- Steps in Conducting Principal Component Analysis
- An Example with Three Retained Components
- Conclusion
Appendix: Assumptions Underlying Principal Component
Analysis
References
Chapter 2 Exploratory Factor Analysis
- Introduction: When Is Exploratory Factor Analysis
- Appropriate?
- Introduction to the Common Factor Model
- Exploratory Factor Analysis versus Principal Component
- Analysis
- Preparing and Administering the Investment Model
- Questionnaire
- SAS Program and Analysis Results
- Steps in Conducting Exploratory Factor Analysis
- A More Complex Example: The Job Search Skills Questionnaire
- Conclusion
Appendix: Assumptions Underlying Exploratory Factor Analysis
References
Chapter 3 Assessing Scale Reliability with Coefficient Alpha
- Introduction: The Basics of Scale Reliability
- Coefficient Alpha
- Assessing Coefficient Alpha with PROC CORR
- Summarizing the Results
- Conclusion
- References
Chapter 4 Path Analysis with Manifest Variables
- Introduction: The Basics of Path Analysis
- Example 1: A Path-Analytic Investigation of the Investment
- Model
- Overview of the Rules for Performing Path Analysis
- Preparing the Program Figure
- Preparing the SAS Program
- Interpreting the Results of the Analysis
- Modifying the Model
- Preparing a Formal Description of the Analysis and Results
- for a Paper
- Example 2: Path Analysis of a Model Predicting Victim
- Reactions to Sexual Harrassmenet
- Conclusion: Learning More about Path Analysis
- References
Chapter 5 Developing Measurement Models with Confirmatory Factor
- Analysis
- Introduction: A Two-Step Approach to Path Analysis with
- Latent Variables
- A Model of the Determinants of Work Performance
- Basic Concepts in Latent-Variable Analyses
- Advantages of Path Analysis with Latent Variables
- Necessary Conditions for Confirmatory Factor Analysis and
- Path Analysis with Latent Variables
- Example: The Investment Model
- Testing the Fit of the Measurement Model from the Investment
- Model Study
- Conclusion: On to Path Analysis with Latent Variables?
- References
Chapter 6 Path Analysis with Latent Variables
- Recapitulation: Basic Concepts in Path Analysis with Latent
- Variables
- Testing the Fit of the Theoretical Model from the Investment
- Model Study
- Preparing a Formal Description of Results for a Paper
- Additional Examples
- Conclusion: Learning More about Latent Variable Models
- References
Appendix A.1 Introduction to SAS Programs, SAS Logs, and SAS Output
Introduction: What is the SAS System?
Three Types of SAS Systems Files
Conclusion
Appendix A.2 Data Input
Introduction: Inputting Questionnaire Data versus Other Types
of Data
Keying Data: An Illustrative Example
Inputting Data Using the CARDS Statement
Additional Guidelines
Inputting a Correlation or Covariance Matrix
Inputting Data Using the INFILE Statement Rather than the CARDS
Statement
Controlling the Size of the Output and Log Pages with the OPTIONS
Statement
Conclusion
References
Appendix A.3 Working with Variables and Observations in SAS Data Sets
Introduction: Manipulating, Subsetting, Concatenating, and Merging
Data
Placement of Data Manipulation and Data Subsetting Statements
Data Manipulation
Data Subsetting
A More Comprehensive Example
Concentating and Merging Data Sets
Conclusion
References
Appendix A.4 Exploring Data with PROC MEANS, PROC FREQ, PROC PRINT,
and PROC UNIVARIATE
Introduction: Why Perform Simple Descriptive Analysis
Example: A Revised Volunteerism Survey
Computing Descriptive Statistics with PROC MEANS
Creating Frequency Tables with PROC FREQ
Printing Raw Data with PROC PRINT
Testing for Normality with PROC UNIVARIATE
Conclusion
References
Appendix A.5 Preparing Scattergrams and Computing Correlations
Introduction: When Are Pearson Correlations Appropriate
Interpreting the Coefficient
Linear versus Nonlinear Relationships
Producing Scattergrams with PROC PLOT
Computing Pearson Correlations with PROC CORR
Appendix: Assumptions Underlying the Pearson Correlation
Coefficient
Reference
Appendix B Data Sets
Appendix C Critical Values of the Chi-Square Distribution
Index