A Beginner's Guide to Structural Equation Modeling

by Randall E. Schumacker, Richard G. Lomax

This book reviews correlation and covariance among variables, followed by multiple regression and path analysis techniques to better understand the building blocks of structural equation modeling. The concepts behind measurement models are introduced to illustrate how measurement error impacts statistical analyses, and structural models are presented that indicate how latent variable relationships can be established. The modeling examples are presented using either EQS 5.0 or LISREL8-SIMPLIS, both of which have an easy-to-use set of commands to specify measurement and structural models. The authors focus on the steps taken in analyzing theoretical models:
* specifying a model based upon theory or prior research;
* determining whether the model can be identified to have unique estimates for variables in the model;
* selecting an appropriate estimation method;
* testing the model and interpreting fit indices; and
* respecifying a model based upon suggested modification indices, which involves adding or dropping paths in the model to obtain a better model fit.
Not intended as an in-depth presentation of statistics or factor analysis, this text focuses on the basic ideas and principles behind structural equation modeling. It assumes a basic understanding of correlation.

Genres: Textbooks, Reference, Economics

304 pages, Paperback

First published June 1, 1996

About the author

Randall E. Schumacker received his Ph.D. in educational psychology from Southern Illinois University. He is currently professor of educational research at the University of North Texas, where he teaches courses in structural equation modeling, quantitative research methodology, statistical simulation, and measurement. His research focuses are varied, including best model selection methods, robust statistics, teacher accountability, and measurement issues related to ability estimation, mixed-item formats, and reliability. He has published in several journals including Academic Medicine, Educational and Psychological Measurement, Journal of Applied Measurement, Journal of Educational and Behavioral Statistics, Journal of Research Methodology, Multiple Linear Regression Viewpoints, and Structural Equation Modeling. He has served on the editorial boards of numerous journals and is a member of the American Educational Research Association and American Psychological Association-Division 5, and is past president of the Southwest Educational Research Association, and emeritus editor of the journal Structural Equation Modeling.