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Doody's Review ServiceReviewer: 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.