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

被引:79
作者
Wei, Yinghui [1 ]
Higgins, Julian P. T. [1 ]
机构
[1] Inst Publ Hlth, MRC Biostat Unit, Cambridge CB2 0SR, England
基金
英国医学研究理事会;
关键词
multivariate meta-analysis; correlated outcomes; nested events; delta method; within-study correlation; MODEL; BIAS;
D O I
10.1002/sim.5679
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 (c) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:1191 / 1205
页数:15
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