Meta-analysis of binary outcomes via generalized linear mixed models: a simulation study.

ABSTRACT:

Background

Systematic reviews and meta-analyses of binary outcomes are widespread in all areas of application. The odds ratio, in particular, is by far the most popular effect measure. However, the standard meta-analysis of odds ratios using a random-effects model has a number of potential problems. An attractive alternative approach for the meta-analysis of binary outcomes uses a class of generalized linear mixed models (GLMMs). GLMMs are believed to overcome the problems of the standard random-effects model because they use a correct binomial-normal likelihood. However, this belief is based on theoretical considerations, and no sufficient simulations have assessed the performance of GLMMs in meta-analysis. This gap may be due to the computational complexity of these models and th

SUBMITTER: Bakbergenuly I 

PROVIDER: S-EPMC6032567 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature