Confirmatory Factor Analysis for Applied Research (Methodology in the Social Sciences Series)

A very helpful text for connecting my graduate instruction in CFA in 1994 to today's conceptual issues and the practical problems of running the analyses. The annotated computer input program file examples helped me link up LISREL 2 with where the analyses are today in LISREL 9.1. In the 20 years, common problems are now able to easily addressed with computer software and that's perfect for me: a researcher who is familiar with the major issues but needs to "brush up" on newer approaches to the older, vexing problems. The later chapters shed more light on higher order and bi-level factor models, which were not even attempted in earlier texts of the day. The earlier chapters present a more systematic presentation of the basic tenets of CFA. This text has already been of great use to me as I seek to use CFA to address applied issues in to the measurement of human performance using video simulation in the field of education.

I love this book. The first edition is one of the most dog-eared books on my shelf. I routinely recommend it to doctoral students and colleagues just getting started in trying to figure out the details of exploratory and confirmatory factor analysis. The second edition is even better, with expanded coverage of emerging methodologies like Bayesian estimation of CFA models, exploratory structural equation modeling, etc... Highly recommended.

Needed it for a stats course, but it is a good book.

Fantastic coverage of measurement models and extensions thereof. The author exemplifies the concepts elucidated in the book with examples that illustrate the syntax of various SEM programs (e.g., LISREL). The reader of this book will leave with a thorough knowledge of CFA.

This is a good reference. Slightly pricey I thought.

Helpful.

Great book.

A vital reference for conducting CFAs.

Important book for factor snalysi

Having read quite a lot of literature on CFA/SEM, I wondered whether I should read yet another book on this topic. But Timothy A. Brown's work is a truly worthwhile endeavor, because I rarely, if ever, have read such a concise and comprehensive text on CFA, thus the basis for any SEM, as this one. The text covers all important areas in an accessible way, delivers a critical, yet constructive appraisal of the current state of the field, provides valuable information how to set up, run, and interpret a CFA and also gives detailed syntax for several statical software packages (e.g., Mplus, SAS, SPSS).I can highly recommend this book to graduate students and researchers as well as anyone interested in this statistical area in general.

Congrats to Tim Brown for his revised and extended 2nd edition. This book is a seminal work that eases the understanding and accessability of CFA/SEM-methods with a special knack for Mplus. I found both the syntaxes and examples extremely helpful, although some questions remained to be answered by the Mplus web-forum or the program handbook.An outstanding feature of the narration is Brown's repeated pledge for the use of estimations and models that not only "work and fit the data" but are adapted to the requirements and constraints which arise from the combination of variable types and research questions. Special sections on multiple-group cfas, missing data handling or power analyses add much-needed features to the core topic of applied CFA.I can recommend chapters of these books to students.Note that it might be helpful to visit the books website to be in touch with erratas and syntax examples free to download.

Excellent ouvrage (auteur reconnu dans le petit monde de la statistique en sciences humaines) permettant au lecteur minimalement initié de faire le lien logique entre les modèles factoriels descriptifs classiques (ACP) et les modèles confirmatoires de type Lisrel par exemple. Tout chercheur devrait en avoir un exemplaire dans sa bibliothèque.

A complete and exhaustive book on CFA. Truly recommended for anyone involved in applied research.