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A Beginner's Guide to Structural Equation Modeling

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The second edition features:

a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues.
The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.

304 pages, Paperback

First published June 1, 1996

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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.

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