Confirmatory Factor Analysis for Applied Research, Second Edition: Edition 2

Guilford Publications
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With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). 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 and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website (www.guilford.com/brown3-materials) offers data and program syntax files for most of the research examples, as well as links to CFA-related resources.

New to This Edition
*Updated throughout to incorporate important developments in latent variable modeling.
*Chapter on Bayesian CFA and multilevel measurement models.
*Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables.
*Utilizes the latest versions of major latent variable software packages.
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About the author

Timothy A. Brown, PsyD, is Professor in the Department of Psychology and Director of Research at the Center for Anxiety and Related Disorders at Boston University. He has published extensively in the areas of the classification of anxiety and mood disorders, the psychopathology and risk factors of emotional disorders, psychometrics, and applied research methods. In addition to conducting his own grant-supported research, Dr. Brown serves as a statistical investigator or consultant on numerous federally funded research projects. He has been on the editorial boards of several scientific journals, including a longstanding appointment as Associate Editor of the Journal of Abnormal Psychology.
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Additional Information

Publisher
Guilford Publications
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Published on
Dec 29, 2014
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Pages
462
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ISBN
9781462517817
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Best For
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Language
English
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Genres
Business & Economics / Statistics
Education / Statistics
Medical / Nursing / Research & Theory
Psychology / Statistics
Social Science / Statistics
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Content Protection
This content is DRM protected.
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Eligible for Family Library

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Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by exercises with answers, rules to remember, and topic boxes. The companion website supplies data, syntax, and output for the book's examples--now including files for Amos, EQS, LISREL, Mplus, Stata, and R (lavaan).

New to This Edition
*Extensively revised to cover important new topics: Pearl's graphing theory and the SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more.
*Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping.
*Expanded coverage of psychometrics.
*Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan).
*Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models.

Pedagogical Features
*Exercises with answers, plus end-of-chapter annotated lists of further reading.
*Real examples of troublesome data, demonstrating how to handle typical problems in analyses.
*Topic boxes on specialized issues, such as causes of nonpositive definite correlations.
*Boxed rules to remember.
*Website promoting a learn-by-doing approach, including syntax and data files for six widely used SEM computer tools.
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