Estimating within‐study covariances in multivariate meta‐analysis with multiple outcomes

Yinghui Wei*, Julian Pt Higgins

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

<jats:p>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. Copyright © 2012 John Wiley &amp; Sons, Ltd.</jats:p>
Original languageEnglish
Pages (from-to)1191-1205
Number of pages0
JournalStatistics in Medicine
Volume32
Issue number7
Early online date3 Dec 2012
DOIs
Publication statusPublished - 30 Mar 2013

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