Multivariate meta-analysis of mixed outcomes: a Bayesian approach.

ABSTRACT: Multivariate random effects meta-analysis (MRMA) is an appropriate way for synthesizing data from studies reporting multiple correlated outcomes. In a Bayesian framework, it has great potential for integrating evidence from a variety of sources. In this paper, we propose a Bayesian model for MRMA of mixed outcomes, which extends previously developed bivariate models to the trivariate case and also allows for combination of multiple outcomes that are both continuous and binary. We have constructed informative prior distributions for the correlations by using external evidence. Prior distributions for the within-study correlations were constructed by employing external individual patent data and using a double bootstrap method to obtain the correlations between mixed outcomes. The between-st

SUBMITTER: Bujkiewicz S 

PROVIDER: S-EPMC4015389 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature