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

Yinghui Wei, Julian Pt Higgins

Research output: Contribution to journalArticle (Academic Journal)peer-review

77 Citations (Scopus)


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 & Sons, Ltd.
Original languageEnglish
JournalStatistics in Medicine
Publication statusPublished - 2012

Bibliographical note

Copyright © 2012 John Wiley & Sons, Ltd.


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