Please use this identifier to cite or link to this item: https://doi.org/10.1080/10705511.2013.797827
Title: Multivariate Meta-Analysis as Structural Equation Models
Authors: Cheung, M.W.-L. 
Keywords: mixed-effects model
multivariate effect sizes
multivariate meta-analysis
random-effects model
structural equation model
Issue Date: Jul-2013
Citation: Cheung, M.W.-L. (2013-07). Multivariate Meta-Analysis as Structural Equation Models. Structural Equation Modeling 20 (3) : 429-454. ScholarBank@NUS Repository. https://doi.org/10.1080/10705511.2013.797827
Abstract: Multivariate meta-analysis has become increasingly popular in the educational, social, and medical sciences. It is because the outcome measures in a meta-analysis can involve more than one effect size. This article proposes 2 mathematically equivalent models to implement multivariate meta-analysis in structural equation modeling (SEM). Specifically, this article shows how multivariate fixed-, random- and mixed-effects meta-analyses can be formulated as structural equation models. metaSEM (a free R package based on OpenMx) and Mplus are used to implement the proposed procedures. A real data set is used to illustrate the procedures. Formulating multivariate meta-analysis as structural equation models provides many new research opportunities for methodological development in both meta-analysis and SEM. Issues related to and extensions on the SEM-based meta-analysis are discussed. © 2013 Copyright Taylor and Francis Group, LLC.
Source Title: Structural Equation Modeling
URI: http://scholarbank.nus.edu.sg/handle/10635/125323
ISSN: 10705511
DOI: 10.1080/10705511.2013.797827
Appears in Collections:Staff Publications

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