Statistical Methods for Quantifying Between-study Heterogeneity in Meta-analysis with Focus on Rare Binary Events
Chiyu Zhang, Min Chen, Xinlei Wang
Abstract
. However, most are incomplete, only including a limited subset of existing methods, and some are outdated. Further, none of the studies covers descriptive measures for assessing the level of heterogeneity, nor are they focused on rare binary events that require special attention. We summarize by far the most comprehensive set including 11 descriptive measures, 23 estimators, and 16 confidence intervals. In addition to providing synthesized information, we further categorize these methods according to their key features. We then evaluate their performance based on simulation studies that examine various realistic scenarios for rare binary events, with an illustration using a data example of a gestational diabetes meta-analysis. We conclude that there is no uniformly "best" method. However, methods with consistently better performance do exist in the context of rare binary events, and we provide practical guidelines based on numerical evidences.