title: Estimating within-study covariances in multivariate meta-analysis with multiple outcomes.
abstract: Multivariate meta-analysis allows the joint synthesis of effect estimates based on multiple outcomes from multiple studies, accounting for the potential correlations among them. However, standard methods for multivariate meta-analysis for multiple outcomes are restricted to problems where the within-study correlation is known or where individual participant data are available. This paper proposes an approach to approximating the within-study covariances based on information about likely correlations between underlying outcomes. We developed methods for both continuous and dichotomous data and for combinations of the two types. An application to a meta-analysis of treatments for stroke illustrates the use of the approximated covariance in multivariate meta-analysis with correlated outcomes.
authors.affiliation: MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 0SR, UK. y.wei@ctu.mrc.ac.uk
authors.forename: Yinghui
authors.initials: Y
authors.lastname: Wei
authors.forename: Julian P T
authors.initials: JP
authors.lastname: Higgins
mesh_terms: D056808:Biostatistics; D002317:Cardiovascular Agents / Q000627:therapeutic use; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D015999:Multivariate Analysis; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D020521:Stroke / Q000188:drug therapy; D016896:Treatment Outcome
chemical_list: D002317:Cardiovascular Agents