Please use this identifier to cite or link to this item: https://doi.org/10.1080/10705511.2013.797827
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dc.titleMultivariate Meta-Analysis as Structural Equation Models
dc.contributor.authorCheung, M.W.-L.
dc.date.accessioned2016-07-08T09:25:32Z
dc.date.available2016-07-08T09:25:32Z
dc.date.issued2013-07
dc.identifier.citationCheung, 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
dc.identifier.issn10705511
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/125323
dc.description.abstractMultivariate 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/10705511.2013.797827
dc.sourceScopus
dc.subjectmixed-effects model
dc.subjectmultivariate effect sizes
dc.subjectmultivariate meta-analysis
dc.subjectrandom-effects model
dc.subjectstructural equation model
dc.typeArticle
dc.contributor.departmentPSYCHOLOGY
dc.description.doi10.1080/10705511.2013.797827
dc.description.sourcetitleStructural Equation Modeling
dc.description.volume20
dc.description.issue3
dc.description.page429-454
dc.identifier.isiut000327839500004
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