Confirmatory Factor Analysis for Applied Research  book cover
2nd Edition

Confirmatory Factor Analysis for Applied Research

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ISBN 9781462515363
Published March 4, 2015 by Guilford Press
462 Pages

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Book Description

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 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.

Table of Contents

l. 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


Descriptive Goodness-of-Fit Indices

Absolute Fit

Parsimony Correction

Comparative Fit

Guidelines for Interpreting Goodness-of-Fit Indices


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


Interpretation and Calculation of CFA Model Parameter Estimates

CFA Models with Single Indicators

Reporting a CFA Study


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

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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.


"Brown's writing is excellent; this book does a clearer and better job of explaining CFA concepts than any other I have read. It has had a very positive impact on the quality of applied CFA studies in the social and behavioral sciences. I will continue to use the second edition in my graduate measurement theory course; it enables my students to greatly improve the quality of their dissertation research. This is the best book I've seen for providing graduate students with the skills they need to develop and evaluate measures of psychological constructs."--G. Leonard Burns, PhD, Department of Psychology, Washington State University

"I am a big fan of this book. When something goes wrong in SEM, it is almost always due to a faulty measurement model, so students need to have a thorough understanding of latent trait measurement models before learning how to evaluate structural models. That is why this book is so important. My students regularly comment on how accessible the text is. I very much like the examples of study results, which students can use as templates for their own reports. The numerically worked examples throughout are extremely helpful at demystifying the process."--Lesa Hoffman, PhD, Institute for Lifespan Studies, University of Kansas

"This book occupies a unique and important position in the field. It describes the use of CFA to address a wide range of important social science research questions that are too often ignored or underdeveloped in books on structural equation modeling. The text helps readers understand the nuances of CFA in a way that is deep yet incredibly accessible. I highly recommend this book to students and experienced social scientists interested in applying this powerful approach in their research."--Noel A. Card, PhD, Department of Educational Psychology, University of Connecticut

"The most comprehensive reference text on CFA for experienced researchers. Other texts typically devote a chapter or two to the subject, but Brown’s coverage is wide and deep. Frankly, what gives this book value to me is that it is a reference text that can be used for instruction. Aided by clear examples, simplified tables, and helpful visual depictions, readers easily gain an understanding of how to run popular modeling software and correctly interpret the output. Perhaps one of the finest jewels in this book is the explanation of non-positive definite matrices, the bane of LISREL users. I also find the thread throughout the book on explaining equivalent models very important."--Randall MacIntosh, PhD, Professor of Sociology, California State University, Sacramento

"I highly recommend this book to colleagues and students who teach and apply structural equation modeling. The book provides an invaluable resource for applied researchers concerning concepts, procedures, and problems in CFA, as well as how to interpret and report analysis results. An especially valuable feature is the many detailed examples that are worked out in detail and presented along with syntax and output from leading software packages. The Appendices at the end of several chapters expand on many technical points the reader might fail to grasp otherwise."--James G. Anderson, PhD, Department of Sociology, Purdue University

"The book does an excellent job of walking through the steps in an analysis. It is wonderfully user friendly in the way it presents each step, discusses major decisions to be made, and presents code and output. Not only do I think this is the best book out there for learning CFA, but I also think it is a fantastic way to learn introductory structural equation modeling methods."--Scott J. Peters, PhD, Department of Educational Foundations, University of Wisconsin-Whitewater

"A strength of this book is the style of the author's presentation. Many important concepts are explained in plain language, rather than by mathematical formula. The book reads as though you were listening to a lecture. It provides the learner with an extensive understanding of the theory and applications of CFA. I also strongly recommend this book to practitioners who are in need of a comprehensive reference for better applications of CFA."--Akihito Kamata, PhD, Department of Education Policy and Leadership and Department of Psychology, Southern Methodist University