Confirmatory Factor Analysis For Applied Research Second Edition
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Confirmatory Factor Analysis for Applied Research, Second Edition
Author: Timothy A. Brown
language: en
Publisher: Guilford Publications
Release Date: 2015-01-08
This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...
Assessing Measurement Invariance for Applied Research
Author: Craig S. Wells
language: en
Publisher: Cambridge University Press
Release Date: 2021-06-03
This book focuses on the practical application of statistical techniques for assessing measurement invariance with less emphasis on theoretical development or exposition. Instead, it describes the methods using a pedagogical framework followed by extensive illustrations that demonstrate how to use software to analyze real data. The chapters illustrate the practical methods to assess measurement invariance and shows how to apply them to a range of data. The computer syntax and data sets used in this book are available for download here: people.umass.edu/cswells.
Confirmatory Factor Analysis for Applied Research
Emphasizing practical and theoretical aspects of confirmatory factor analysis (CFA) rather than mathematics or formulas, Timothy A. Brown uses rich examples derived from the psychology, management, and sociology literatures to provide in-depth treatment of the concepts, procedures, pitfalls, and extensions of CFA methodology. Chock full of useful advice and tables that outline the procedures, the text shows readers how to conduct exploratory factor analysis (EFA) and understand similarities to and differences from CFA; formulate, program, and interpret CFA models using popular latent variable software packages such as LISREL, Mplus, Amos, EQS, and SAS/CALIS; and report results from a CFA study. Also covered are extensions of CFA to traditional IRT analysis, methods for determining necessary sample sizes, and new CFA modeling possibilities, including multilevel factor models and factor mixture models. Special features include a Web page offering data and program syntax files for many of the research examples so that readers can practice the procedures described in the book with real data. The Web page also includes links to additional CFA-related resources.