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Confirmatory factor analysis for applied research / Timothy A. Brown

Author
Brown, Timothy A., 1960-
Published
New York : Guilford Publications, 2015.
Edition
Second edition.
Physical Description
1 online resource (482 pages).
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Contents
Machine generated contents note: 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 CFA in Different Software Programs -- Model Evaluation -- Overall Goodness of Fit -- Localized Areas of Strain -- 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.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 -- Intermediate Steps for Further Developing a Measurement Model for CFA -- EFA in the CFA Framework -- Exploratory SEM -- 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 -- The Effects Coding Approach to Scaling Latent Variables -- CFA in Multiple Groups -- Overview of Multiple-Groups Solutions -- Multiple-Groups CFA -- Selected Issues in Single- and Multiple-Groups CFA Invariance Evaluation -- MIMIC Modeling (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 -- Bifactor Models -- Scale Reliability Estimation -- Point Estimation of Scale Reliability -- Standard Error and Interval Estimation of Scale Reliability -- Models with Formative Indicators -- Summary -- 9.Data Issues in CFA: Missing, Non-Normal, and Categorical Data -- CFA with Missing Data -- Mechanisms of Missing Data -- Conventional Approaches to Missing Data -- Recommended Strategies for Missing Data -- CFA with Non-Normal or Categorical Data -- Non-Normal, Continuous Data -- Categorical Data -- Other Potential Remedies for Indicator Non-Normality -- Summary -- 10.Statistical Power and Sample Size -- Overview -- Satorra--Saris Method -- Monte Carlo Approach -- Summary -- Appendix 10.1 Monte Carlo Simulation in Greater Depth: Data Generation -- 11.Recent Developments Involving CFA Models -- Bayesian CFA -- Bayesian Probability and Statistical Inference -- Priors in CFA -- Applied Example of Bayesian CFA -- Bayesian CFA: Summary -- Multilevel CFA -- Summary -- Appendix 11.1 Numerical Example of Bayesian Probability.
Subject(s)
ISBN
9781462517800 electronic bk.
1462517803 electronic bk.
Bibliography Note
Includes bibliographical references and index.
View MARC record | catkey: 16421010