Confirmatory Factor Analysis for Applied Research, First Edition / Edition 1

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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.
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Editorial Reviews

Doody's Review Service
Reviewer: Christopher J Graver, PhD, ABPP-CN(Madigan Healthcare System)
Description: Confirmatory factor analysis is a commonly used statistical technique, but it is often forgotten in the literature. This book provides a comprehensive resource on the use of this technique from methodological approaches to statistical considerations.
Purpose: As part of the Methodology in the Social Sciences series, this book fills a significant gap in the current literature for a text on confirmatory factor analysis. It is intended to do this in a user-friendly way and spares the reader many of the behind-the-scenes complexities that are not critical to know on a day-to-day basis.
Audience: The author intends this book for graduate students and researchers in the social and behavioral sciences (e.g., psychology, sociology, education, political science, etc.). The author has a respectable scholarly record and serves as a statistical consultant on federally funded research projects.
Features: The book begins with an introduction to confirmatory factor analysis for those new to this technique. It then helps readers to run, view, and interpret the data from this technique. Later chapters begin to explore specialized uses of the confirmatory factor analysis. The book ends with chapters addressing data issues (e.g., missing data, non-normality, data parsing) and statistical power and sample size considerations. Each chapter begins with an abstract and ends with a summary, both of which are helpful at a glance. Numerous figures and tables summarize the information and provide example statistical outputs to assist readers. The practical examples aid in comprehending this material from a hands-on point of view.
Assessment: This user-friendly guide to confirmatory factor analysis provides information and examples to help students and researchers through most any methodological situation. An abundance of practical advice on options for analyses, data issues, and reading and interpreting the data output make this a useful guide for almost anyone. Graduate students will find this an especially worthwhile addition to their statistical education and it would be a valuable course textbook for professors.
From the Publisher

"I found the author’s coverage of confirmatory factor analysis (CFA) both clear and accurate. I thought the explanations were pitched at the right level of mathematical and statistical complexity for the intended audience. In fact, the coverage of certain topics/m-/such as the problem of empirical under-identification and the computation of determinants and their functional significance in the assessment of global model fit/m-/is among the best I’ve read. This is a book that students will be glad to have on their shelves when they turn to their own data later on."--Christopher M. Federico, Department of Psychology and Department of Political Science, University of Minnesota

"Compared to other books, this book offers a lot of details which would facilitate better understanding of confirmatory factor analysis (CFA). The author is very good at explaining a lot of processes by examples, and includes clear figures and tables. I definitely recommend it to instructors who teach a course on CFA, especially for students who are not in quantitative psychology."--Ke-Hai Yuan, Department of Psychology, University of Notre Dame

"I confidently recommend this book to any colleague teaching a course in confirmatory factor analysis (CFA), structural equation modeling, or scale development. The text will also be an invaluable resource for applied researchers, due to the quantity and quality of the information it contains. Included are very clear explanations of the 'thick' technical terminology and excellent elaboration on the shortcomings of the previously published CFA research within the past 10-15 years. Other strengths are clearly written chapters on higher order analyses and multitrait-multimethod models; clear coverage of conducting CFA with missing data and conducting reliability analysis within the general framework of SEM, providing a very defensible and unified approach to the issues of reliability and validity during the process of scale/instrument development; and strategies for data screening and dealing with nonnormally distributed data."--Larry Price, Doctoral Program in Education, Texas State University-San Marcos


"For each chapter, Brown provides a comprehensive review of the topic by providing a clear commentary on the issues. He enhances this commentary with equations where necessary, illustrations, and numerical examples....The book delivers on its promise. It provides a comprehensive review of CFA techniques as a collection of essential tools that serve the contemporary researcher....The statistically sophisticated reader is provided with a current review of the appropriate use of these techniques....It could be used in an upper level graduate methodology course or by the active researcher who wishes to expand his or her repertoire of empirical techniques."--PsycCRITIQUES
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Product Details

  • ISBN-13: 9781593852740
  • Publisher: Guilford Publications, Inc.
  • Publication date: 4/21/2006
  • Series: Methodology In The Social Sciences Series
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 475
  • Product dimensions: 5.90 (w) x 8.90 (h) x 1.00 (d)

Meet the Author

Timothy A. Brown is a professor in the Department of Psychology at Boston University (BU), and Director of Research at BU's Center for Anxiety and Related Disorders. He has published extensively in the areas of the classification of anxiety and mood disorders, psychometrics, and methodological advances in social sciences research.
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Table of Contents

1 Introduction 1
2 The common factor model and exploratory factor analysis 12
3 Introduction to CFA 40
4 Specification and interpretation of CFA models 103
5 CFA model revision and comparison 157
6 CFA of multitrait-multimethod matrices 212
7 CFA with equality constraints, multiple groups, and mean structures 236
8 Other types of CFA models : higher-order factor analysis, scale reliability evaluation, and formative indicators 320
9 Data issues in CFA : missing, non-normal, and categorical data 363
10 Statistical power and sample size 412
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  • Anonymous

    Posted June 24, 2011

    Nook Study books don't work on a Nook

    I bought this book as a nook textbook so that I could read it on my nook and take it with me everywhere, but found out that you can only display it on a computer. And I mean absolutely only on a computer. It won't open on my nook, my phone, or my iPad. So be careful. Nook text books are VERY RESTRICTING. If I would have known I would have bought it in paper back.

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