Handling incomplete correlated continuous and binary outcomes in meta-analysis of individual participant data.

ABSTRACT: Meta-analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta-analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta-analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate

SUBMITTER: Gomes M 

PROVIDER: S-EPMC4982066 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature