An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis.

ABSTRACT:

Background

A number of strategies have been proposed to handle missing binary outcome data (MOD) in systematic reviews. However, none of these have been evaluated empirically in a series of published systematic reviews.

Methods

Using published systematic reviews with network meta-analysis (NMA) from a wide range of health-related fields, we evaluated comparatively the most frequently described Bayesian modelling strategies for MOD in terms of log odds ratio (log OR), between-trial variance, inconsistency factor (i.e. difference between direct and indirect estimates for a comparison), surface under the cumulative ranking (SUCRA) and rankings. We extended the Bayesian random-effects NMA model to incorporate the informative missingness odds ratio (IMOR) parameter, and applied t

SUBMITTER: Spineli LM 

PROVIDER: S-EPMC6480793 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature