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|Title:||Multivariate Meta-Analysis as Structural Equation Models||Authors:||Cheung, M.W.-L.||Keywords:||mixed-effects model
multivariate effect sizes
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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