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Meta-analysis. A structural equation modeling approach. (English) Zbl 1311.62002

Hoboken, NJ: John Wiley & Sons (ISBN 978-1-119-99343-8/hbk; 978-1-118-95781-3/ebook). xxi, 378 p. (2015).
Publisher’s description: Presents a novel approach to conducting meta-analysis using structural equation modeling.
Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment.
The book begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included.
This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

MSC:

62-02 Research exposition (monographs, survey articles) pertaining to statistics
62-07 Data analysis (statistics) (MSC2010)
62Pxx Applications of statistics
65C60 Computational problems in statistics (MSC2010)

Software:

R; metaSEM; Mplus
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