Presents a novel technique to conducting meta-analysis using structural equation modeling.
Structural equation modeling (SEM) and meta-analysis are two extremely efficient statistical methods inside the educational, social, behavioral, and medical sciences. They’re sometimes dealt with as two unrelated topics inside the literature. This book presents a unified framework on analyzing meta-analytic data contained in the SEM framework, and illustrates how one can conduct meta-analysis using the metaSEM package deal deal inside the R statistical environment.
Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering evaluation questions. Key ideas in meta-analysis and SEM are briefly reviewed, and quite a few meta-analytic fashions are then launched and linked to the SEM framework. Fixed-, random-, and mixed-outcomes fashions in univariate and multivariate meta-analyses, three-diploma meta-analysis, and meta-analytic structural equation modeling, are launched. Superior topics, harking back to using restricted most chance estimation method and coping with missing covariates, are moreover coated. Readers will research a single framework to make use of every meta-analysis and SEM. Examples in R and in Mplus are included.
This book is perhaps a invaluable helpful useful resource for statistical and academic researchers and graduate school college students ending up meta-analyses, and in addition will probably be useful to researchers and statisticians using SEM in biostatistics. Main info of each SEM or meta-analysis will in all probability be helpful in understanding the provides on this book.
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