Confirmatory Factor Analysis for Applied Research
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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 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
Uses of Confirmatory Factor Analysis
Psychometric Evaluation of Test Instruments Construct Validation
Measurement Invariance Evaluation
Why a Book on CFA?
Coverage of the Book
Summary 2. The Common Factor Model and Exploratory Factor Analysis
Overview of the Common Factor Model
Procedures of EFA
Summary 3. Introduction to CFA
Similarities and Differences of EFA and CFA
Common Factor Model
Standardized and Unstandardized Solutions
Indicator Cross-Loadings/Model Parsimony
Purposes and Advantages of CFA
Parameters of a CFA Model
Fundamental Equations of a CFA Model
CFA Model Identification
Scaling the Latent Variable
Guidelines for Model Identification
Estimation of CFA Model Parameters
Descriptive Goodness-of-Fit Indices
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
Defining the Metric of Latent Variables
Data Screening and Selection of the Fitting Function
Running CFA in Different Software Programs
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
"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