Meta-Analysis Using Structural Equation Modeling

Autorentext

Randall E. Schumacker, PhD, is Professor of Educational Research at The University of Alabama, where he teaches courses in multiple regression, multivariate statistics, and structural equation modeling. He is past president of the Southwest Educational Research Association and Editor Emeritus of Structural Equation Modeling: A Multidisciplinary Journal. Dr. Schumacker has written or edited several books and numerous journal articles. He founded the Structural Equation Modeling Special Interest Group of the American Educational Research Association, and is a recipient of the association's Structural Equation Modeling Service Award.

Klappentext

Filling a gap in the contemporary literature, this practical guide shows how structural equation modeling (SEM) can be used to analyze results from multiple different studies on the same subject. Randall E. Schumacker presents programs using LISREL, Mplus, and R software, complete with worked-through examples, procedural steps, and sample annotated code. He provides an overview of meta-analysis and the basic SEM modeling steps before delving into meta-analysis in path models, confirmatory factor models, and structural equation models (MASEM). The book offers insights into why meta-analysis should be considered a multilevel method since data are collected over several years, making time a nested effect. It discusses key MASEM issues, such as publication bias, sample size differences between studies, and the heterogeneity of effect sizes across studies, and reviews PRISMA reporting guidelines aligned with APA style. Full code and output for the book's examples can be accessed at the companion website.

Inhalt

Preface

1. Historical Overview
2. Literature Search Review
3. Meta-Analysis Software
4. Basic Meta-Analysis Statistics
5. Basic Structural Equation Modeling
6. Meta-Analysis Assumptions, Steps, and Model Types
7. Path Model MASEM
8. Factor Model MASEM
9. Structural Equation Model MASEM
10. Multi-Level Analysis in Meta-Analysis
11. SEM and MASEM Issues
12. Afterword
    References
    Author Index
    Subject Index
    About the Author