Multivariate Meta-analysis

This chapter reviews meta-analytic methods for synthesis of multivariate data to estimate magnitudes of effect across studies, and to examine variation in patterns of outcomes.

Abstract

This chapter reviews meta-analytic methods for synthesis of multivariate data. Meta-analysis, or research synthesis, provides a way to examine results accumulated from a series of related studies, through statistical analyses of those results. The approach to multivariate meta-analysis presented here can be applied regardless of the form of the effect of interest. In general, the goals of a multivariate meta-analysis are the same as those of univariate syntheses: to estimate magnitudes of effect across studies, and to examine variation in patterns of outcomes. Moreover, reviewers have a wide range of options available when faced with multivariate data in meta-analysis. The specific set of analyses a reviewer selects depends on a number of factors. For example, the reviewer must consider the structure of the data in the review. If the multivariate data are a small part of the evidence in the review, it may make sense to use a simple approach, such as dropping or combining outcomes, or using sensitivity analyses to evaluate the impact of the dependence on the results of the review.