Timothy A. Brown PsyD-Confirmatory Factor Analysis for Applied Research, Second

480 Pages·2015·7.89 MB·English

Confirmatory Factor Analysis for Applied Research
Methodology in the Social Sciences
David A. Kenny, Founding Editor
Todd D. Little, Series Editor
www.guilford.com/MSS
This series provides applied researchers and students with analysis and research design books that
emphasize the use of methods to answer research questions. Rather than emphasizing statistical
theory, each volume in the series illustrates when a technique should (and should not) be used and
how the output from available software programs should (and should not) be interpreted. Common
pitfalls as well as areas of further development are clearly articulated.
RECENT VOLUMES
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CONFIRMATORY FACTOR ANALYSIS FOR APPLIED RESEARCh, SECOND EDITION
Timothy A. Brown
Confirmatory Factor Analysis
for Applied Research
SECOND EDITION
Timothy A. Brown
Series Editor’s Note by Todd D. Little
ThE GUILFORD PRESS
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© 2015 The Guilford Press
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All rights reserved
No part of this book may be reproduced, translated, stored in a retrieval
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photocopying, microfilming, recording, or otherwise, without written permission
from the publisher.
Printed in the United States of America
This book is printed on acid-free paper.
Last digit is print number: 9 8 7 6 5 4 3 2 1
Library of Congress Cataloging-in-Publication Data
Brown, Timothy A., 1960–
Confirmatory factor analysis for applied research / Timothy A. Brown. —
Second edition.
pages cm. — (Methodology in the social sciences)
Includes bibliographical references and index.
ISBN 978-1-4625-1779-4 (hardcover) — ISBN 978-1-4625-1536-3 (paperback)
1. Factor analysis. I. Title.
BF39.2.F32B76 2015
150.1′5195354—dc23
2014040687
For my sons, Nick and Greg

Series Editor’s Note
I have taught structural equation modeling (SEM) for over 25 years. For most of those
years, I relied on a set of readings and other resources because I was dissatisfied with
the lack of depth and breadth afforded to the measurement model in the works that were
available at the time. The first edition of Timothy Brown’s Confirmatory Factor Analysis
for Applied Research (2006) was the first book that I required for my courses related to
SEM. In 2006, there was no other book that covered the nuts and bolts of confirmatory
factor analysis (CFA). Not only did Tim’s book fill a crucial void; it did so with acumen
and elegance. Both editions are full treatments that are very accessible, but the second
edition accomplishes two critical goals that make it a must-have. First, it retains the
accessible nature and applied focus that made the first edition a great read and thorough
resource. Second, as a scholar of methodology and statistics, Tim has provided critical
updates and integrated the most recent advances in the area. A lot of new ideas have
emerged in the past decade, and Tim has gleaned the important advances from the lit-
erature and woven them into the fabric of his masterful tapestry.
The material covered in Tim’s book represents about 90% of the effort and knowl-
edge that are needed and utilized in conducting an SEM analysis. Somewhat ironically, it
represents only about 10% of what is actually presented in the results section of a paper
(i.e., all the foundational issues associated with properly specifying and estimating the
measurement model). This material is the stuff behind the scenes that shines the spot-
light on your analyses—like all the credits that scroll at the end of an award-winning
movie. Tim’s treatise is itself award worthy.
As an amazingly accomplished applied researcher, Tim understands the needs of
researchers who are in the trenches doing the hard work of behavioral science research.
Graduate students just learning advanced statistical techniques will relish the compre-
hensive coverage of all things CFA (e.g., Bayesian approaches, non-normal and categori-
cal indicators, multitrait–multimethod models, factorial invariance—heck, just check
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viii Series Editor’s Note
out the subject index, and you’ll be hard pressed to find an important topic that is miss-
ing!). As a gold standard for specifying and estimating the measurement model for a
subsequent SEM analysis, this book will serve as a constant source for solving an applied
problem.
When you read Tim’s book, you’ll notice he makes some recommendations that I
don’t make in my book, Longitudinal Structural Equation Modeling, and vice versa. I think
it is important to understand that there is no one correct way to do SEM. It is always a
matter of wise judgment and principled reasoning. Tim Brown is wise, and his reason-
ing is clear. Unlike too many pundits, Tim does not try to teach you what to think about
CFA, but rather how to think about CFA. Learning to have civil dialogues with data,
analysis models, and theories is the ultimate learning goal. Tim Brown’s book is a Com-
munication 101 requirement for applied researchers using CFA.
As the founding steward of this series, David A. Kenny, intimated in his introduc-
tion to the first edition, Tim does not lead with formulas, equations, and mathematics—
but he does not shy away from explaining essential complexity. His ability to reach you
as an applied researcher is a balance of the calculus of detail versus clarity. Tim Brown’s
balance of these two forces in his second edition is perfect.
Todd d. LiTTLe
Texas Tech University
Founding Director of the Institute for Measurement, Methodology,
Analysis, and Policy (IMMAP)
On assignment in San José, Costa Rica
Preface
The first edition of this book was written for the simple reason that no other book of
its kind had been published before. This statement continues to be true at this writ-
ing. Whereas the number of texts on structural equation modeling (SEM) continues
to expand, this volume remains the first and only book devoted solely to the topic of
confirmatory factor analysis (CFA). In the first edition, many important topics were
brought into one volume, including the similarities and differences of exploratory fac-
tor analysis (EFA) and CFA; methods to move successfully from the EFA to the CFA
framework; diagnosing and rectifying the various sources for the ill fit of measurement
models; analysis of mean structures; modeling with multiple groups or multiple assess-
ment points; CFA-based scale reliability evaluation; formative indicator models; and
higher-order factor analysis. After covering the fundamentals of specifying, revising,
and interpreting various types of CFA measurement models in the first several chap-
ters, subsequent chapters dealt with issues germane to latent variable models of any
type (e.g., modeling with non-normal or categorical indicators, dealing with missing
data, and power analysis/sample size determination). This material was included not
only because of its importance to the proper conduct of CFA, but because these topics
have not received adequate coverage in other SEM sourcebooks. Thus this book should
continue to serve as a useful guide to researchers working with a latent variable model
of any type.
Although the aforementioned topics remain essential to applied CFA research, it
was important to revise this book to incorporate the latest developments in latent vari-
able modeling. Accordingly, existing chapters have been updated and expanded to cover
several new methodological advances. These new topics include exploratory SEM (a
more contemporary and advantageous method of moving from EFA to CFA, or as a bet-
ter approach to measurement model evaluation when traditional CFA specification is
not realistic); bifactor modeling (an alternative approach to evaluating the hierarchical/
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