Confirmatory Factor Analysis

✍ Scribed by J. Micah Roos; Shawn Bauldry

• Publisher: Quantitative Applications in t
• Year: 2021
• Tongue: English
• Leaves: 145
• Category: Library

✦ Synopsis

Measurement connects theoretical concepts to what is observable in the empirical world, and is fundamental to all social and behavioral research. In this volume, J. Micah Roos and Shawn Bauldry introduce a popular approach to measurement: Confirmatory Factor Analysis (CFA). As the authors explain, CFA is a theoretically informed statistical framework for linking multiple observed variables to latent variables that are not directly measurable. The authors begin by defining terms, introducing notation, and illustrating a wide variety of measurement models with different relationships between latent and observed variables. They proceed to a thorough treatment of model estimation, followed by a discussion of model fit. Most of the volume focuses on measures that approximate continuous variables, but the authors also devote a chapter to categorical indicators. Each chapter develops a different example (sometimes two) covering topics as diverse as racist attitudes, theological conservatism, leadership qualities, psychological distress, self-efficacy, beliefs about democracy, and Christian nationalism drawn mainly from national surveys. Data to replicate the examples are available on a companion website, along with code in R, Stata, and Mplus.

✦ Table of Contents

Cover
Contents
Series Editor’s Introduction
Preface
Acknowledgments
About the Authors
Chapter 1. Introduction
1.1 Latent and Observed Variables
1.2 Reliability and Validity
1.3 Confirmatory Factor Analysis
1.4 Statistical Software and Code
1.5 Outline of the Book
1.6 Further Reading
Chapter 2. Model Specification
2.1 Forms of CFA Measurement Models
2.2 Conclusion
2.3 Further Reading
Chapter 3. Identification and Estimation
3.1 Identification
3.2 Estimation
3.3 Conclusion
3.4 Further Reading
Chapter 4. Model Evaluation and Respecification
4.1 Model Evaluation
4.2 Comparing Models
4.3 Model Respecification
4.4 Conclusion
4.5 Further Reading
Chapter 5. Measurement Invariance
5.1 Multiple-Groups CFA
5.2 MIMIC Models
5.3 Conclusion
5.4 Further Reading
Chapter 6. Categorical Indicators
6.1 Conceptualization of Ordinal Measures
6.2 Estimators
6.3 Model Fit and Parameter Interpretation
6.4 ComparisonWith IRT Models
6.5 Conclusion
6.6 Further Reading
Chapter 7. Conclusion
7.1 Advanced Topics in CFA
7.2 Moving Beyond CFA
Chapter 8. Appendix: Reliability of Scales
Chapter 9. Glossary
References
Index