A Beginner's Guide to Structural Equation Modeling: Third Edition

by Randall E. Schumacker, Richard G. Lomax

This best-seller introduces readers to structural equation modeling (SEM) so they can conduct their own analysis and critique related research. Noted for its accessible, applied approach, chapters cover basic concepts and practices and computer input/output from the free student version of Lisrel 8.8 in the examples. Each chapter features an outline, key concepts, a summary, numerous examples from a variety of disciplines, tables, and figures, including path diagrams, to assist with conceptual understanding. The book first reviews the basics of SEM, data entry/editing, and correlation. Next the authors highlight the basic steps of model specification, identification, estimation, testing, and modification, followed by issues related to model fit and power and sample size. Chapters 6 through 10 follow the steps of modeling using regression, path, confirmatory factor, and structural equation models. Next readers find a chapter on reporting SEM research including a checklist to guide decision-making, followed by one on model validation. Chapters 13 through 16 provide examples of various SEM model applications. The book concludes with the matrix approach to SEM using examples from previous chapters. Highlights of the new edition Designed for introductory graduate level courses in structural equation modeling or factor analysis taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. An understanding of correlation is assumed. To access the website visit the book page or the Textbook Resource page at for more details.

Genres: Textbooks, Reference, Economics

536 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.