Random-effects meta-analysis models for pooling rare events data: a comparison between frequentist and bayesian methods.

ABSTRACT:

Background

Standard random-effects meta-analysis models for rare events exhibit significant limitations, particularly when synthesizing studies with double-zero events. While methodological advances in both frequentist and Bayesian frameworks now offer robust alternatives that bypass continuity corrections, the comparative performance of these approaches-especially between Bayesian and frequentist paradigms-remains understudied.

Methods

This study evaluates the performance of ten widely used meta-analysis models for binary outcomes, using the odds ratio as the effect measure. The evaluated models comprise seven frequentist and three Bayesian approaches. Simulations systematically varied key parameters, including control event rates, treatment effects, study numbers, and hete

SUBMITTER: Yao M 

PROVIDER: S-EPMC12492550 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature