Advanced structural equation modeling : issues and techniques

375 Pages·1996·9.82 MB·English

by  Marcoulides, George A., Schumacker, Randall E

Edited by
George A. Marcoulides
Randall E. Schumacker
Advanced Structural
Equation Modeling
Issues and Techniques
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Advanced Structural
Equation Modeling
Issues and Techniques
Edited by
George A. Marcoulides
California State University, Fullerton
Randall E. Schumacker
University of North Texas
vp Psychology Press
Taylor & I rancis Croup
New York London
First Published by
Lawrence Erlbaum Associates, Inc., Publishers
10 Industrial Avenue
Mahwah, New Jersey 07430-2262
Transferred to Digital Printing 2009 by Psychology Press
270 Madison Ave, New York NY 10016
27 Church Road, Hove, East Sussex, BN3 2FA
Copyright © 1995 l>y Lawrence Erlbaum Associates, Inc.
All rights reserved. No part of this book may be reproduced in
any form, by photostat, microfilm, retrieval system, or any other
means, without the prior written permission of the publisher.
Cover design by Gail Silverman
Library of Congress Cataloging-in-Publication Data
Advanced structural equation modeling : issues and techniques / edited
by George A. Marcoulides, Randall E. Schumacker.
p. cm.
Includes bibliographical references and index.
ISBN 0-8058-1819-7
1. Multivariate analysis. 2. Social sciences—Statistical
methods. 1. Marconi ides, George A. II. Schumacker. Randall E.
QA278A27 1996
519.5'35—dc20 95^34310
CIP
Publisher’s Note
The publisher has gone to great lengths to ensure the quality of this reprint
but points out that some imperfections in the original may he apparent.
Contents
Acknowledgments
1 Introduction
George <4. Marcoulides and Randall E. Schumar.ker
2 Models for Multitrail— Multimethod Matrix Analysis
Werner Wothke
9, Nonlinear Stmctural Equation Models:
The Kcnny-Judd Model With Interaction Effects
Karl G. Joreskog and Fan Yang
4 Multilevel Models From a Multiple Croup Structural
Equation Perspective
John ]. McArdle and Fumiaki Hamagami
5 Cross-Domain Analyses of Change Over Time:
Combining Growth Modeling and
Covariance Structure Analysis
John B. Willett and Aline G. Sayer
vi CONTENTS
6 A Hierarchy of Univariate and Multivariate
Structural Times Series Models 159
Scott L. HershJierger, Peter C. M. Molenaar,
and Sherry E. Comeal
1 IJootstrapping Techniques in Analysis of Mean
and Covariance Structures 195
Yiu-Fai Yung and Peter M. Rent bn
8 A Limiled-Information Estimator for LISREL Models
With or Without Heteroscedastic Errors 227
Kenneth >4. Bollen
9 Full Information Estimation in the Presence
of Incomplete Data 243
James L Arbuckle
10 Inference Problems With Equivalent Models 279
Larry J. Williams, Hamparsum Bo-Aogan,
and Lynda Aiman-Smilh
11 An Evaluation of Incremental Fit Indices:
A Clarification of Mathematical and Empirical
Properties 315
Herbert W. Marsh, John R Balia, and Kit-Tai Hau
Author Index 355
Subjcct Index 361
About the Authors 363
Acknowledgments
We would like to thank all of the contributors for their time and effort in
preparing chapters for this volume. They all provided excellent chapters
and the authors worked diligently with us through the various stages of the
publication proccss. Without them, this volume would not exist. We would
also like to thank Larry Erlbaum, Judith Amsel, Kathleen Dolan, Kathryn
Scornavacca, and the rest of the editorial staff at Lawrence Erlbaum Asso­
ciates for their assistance and support in putting together this volume. Fi­
nally, we thank our families for their love and for enduring yet another
project.
—Geurge A. Marcoulides
—Randall E. Schumacker
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CHAPTER ONE
Introduction
George A. Marcoulides
California Slate University, Fullerton
Randall E. Schumacker
University of North Texas
Structural equation models (SF.Ms) are used hv biologists, educational re­
searchers, market researchers, medical researchers, psychologists, social sci­
entists, and others who traditionally deal with nonexperimental and
quasi-experiinental data. One reason for the pervasive use in almost every
scientific field of study is that SEMs provide researchers with a comprehen­
sive method for the quantification and testing of theories. In fact., it has
been suggested that the development of SEM is perhaps the most important
and influential statistical revolution to have recently occurred in the scien­
tific arena (Cliff, 1983).
SEM techniques are accepted today as a major component of applied
multivariate analysis. The use of the term structural equation modeling is
broadly defined to accomodate models that include latent variables, meas­
urement errors in both dependent and independent variables, multiple
indicators, reciprocal causation, simultaneity, and interdependence. As im­
plemented in most commercial computer packages (e.g., Amos, EQS, LIS-
REL, LISCOMP, Mx, SAS PROC-CAUS, ST ATI ST ICA-SEPAT H), the
method includes as special cases such procedures as confirmatory factor
analysis, multiple regression, path analysis, models for time-dependent
data, recursive and nonrccursive models for cross-sectional and longitutinal
data, and covariance structure analysis.
The purpose of this volume is to introduce the latest issues and devel­
opments in SEM techniques. The goal is to provide an understanding and
working knowledge of advanced SEM techniques with a minimum of
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