Contents 1. Introduction Uses of Confirmatory Factor Analysis Psychometric Evaluation of Test Instruments Construct Validation Method Effects Measurement Invariance Evaluation Why a Book on CFA? Coverage of the Book Other Considerations Summary 2. The Common Factor Model and Exploratory Factor Analysis Overview of the Common Factor Model Procedures of EFA Factor Extraction Factor Selection Factor Rotation Factor Scores Summary 3. Introduction to CFA Similarities and Differences of EFA and CFA Common Factor Model Standardized and Unstandardized Solutions Indicator Cross-Loadings/Model Parsimony Unique Variances Model Comparison Purposes and Advantages of CFA Parameters of a CFA Model Fundamental Equations of a CFA Model CFA Model Identification Scaling the Latent Variable Statistical Identification Guidelines for Model Identification Estimation of CFA Model Parameters Illustration Descriptive Goodness-of-Fit Indices Absolute Fit Parsimony Correction Comparative Fit Guidelines for Interpreting Goodness-of-Fit Indices Summary Appendix 3.1. Communalities, Model-Implied Correlations, and Factor Correlations in EFA and CFA Appendix 3.2. Obtaining a Solution for a Just-Identified Factor Model Appendix 3.

3. Hand Calculation of FML for the Figure 3.8 Path Model 4. Specification and Interpretation of CFA Models An Applied Example of a CFA Measurement Model Model Specification Substantive Justification Defining the Metric of Latent Variables Data Screening and Selection of the Fitting Function Running the CFA Analysis Model Evaluation Overall Goodness of Fit Localized Areas of Strain Residuals Modification Indices Unnecessary Parameters Interpretability, Size, and Statistical Significance of the Parameter Estimates Interpretation and Calculation of CFA Model Parameter Estimates CFA Models with Single Indicators Reporting a CFA Study Summary Appendix 4.1. Model Identification Affects the Standard Errors of the Parameter Estimates Appendix 4.2. Goodness of Model Fit Does Not Ensure Meaningful Parameter Estimates Appendix 4.

3. Example Report of the Two-Factor CFA Model of Neuroticism and Extraversion 5. CFA Model Revision and Comparison Goals of Model Respecification Sources of Poor-Fitting CFA Solutions Number of Factors Indicators and Factor Loadings Correlated Errors Improper Solutions and Nonpositive Definite Matrices EFA in the CFA Framework Model Identification Revisited Equivalent CFA Solutions Summary 6. CFA of Multitrait-Multimethod Matrices Correlated versus Random Measurement Error Revisited The Multitrait-Multimethod Matrix CFA Approaches to Analyzing the MTMM Matrix Correlated Methods Models Correlated Uniqueness Models Advantages and Disadvantages of Correlated Methods and Correlated Uniqueness Models Other CFA Parameterizations of MTMM Data Consequences of Not Modeling Method Variance and Measurement Error Summary 7. CFA with Equality Constraints, Multiple Groups, and Mean Structures Overview of Equality Constraints Equality Constraints within a Single Group Congeneric, Tau-Equivalent, and Parallel Indicators Longitudinal Measurement Invariance CFA in Multiple Groups Overview of Multiple-Groups Solutions Multiple-Groups CFA Selected Issues in Single- and Multiple-Groups CFA Invariance Evaluation MIMIC Models (CFA with Covariates) Summary Appendix 7.1. Reproduction of the Observed Variance- Covariance Matrix with Tau-Equivalent Indicators of Auditory Memory 8. Other Types of CFA Models: Higher-Order Factor Analysis, Scale Reliability Evaluation, and Formative Indicators Higher-Order Factor Analysis Second-Order Factor Analysis Schmid-Leiman Transformation Scale Reliability Estimation