Multivariate Meta-Analysis as Structural Equation Models

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.

Keywords:

• mixed-effects model
• multivariate effect sizes
• multivariate meta-analysis
• random-effects model
• structural equation model

Notes

¹The complete data sets, the Mplus code, and the output are available at http://courses.nus.edu.sg/course/psycwlm/internet/multivariateMA.zip.