Bivariate random-effects meta-analysis and the estimation of between-study correlation.

ABSTRACT:

Background

When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (rhoB).

Methods

In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA). We consider two applied examples, one involving a diagnostic marker and the other a surrogate outcome. These motivate a simulation study where estimation properties from BRMA are compared with those from two separate univariate random-effects meta-analyses (URMAs), the traditional approach.

Results

The normal BRMA model estimate

SUBMITTER: Riley RD 

PROVIDER: S-EPMC1800862 | biostudies-literature | 2007 Jan

REPOSITORIES: biostudies-literature