All Times EDT
Keywords: Meta Analysis, rare events
Examining the safety of new drugs is important in clinical trials. In clinical studies, the occurrence of adverse events (e.g.deaths) is often rare. However, in the case of rare events, a single study may not produce sufficient power to detect meaningful signals. The meta-analysis, which synthesizes multiple studies, is widely used to analyze rare events data. When events are rare, some of the studies may observe zero events in both treatment and control arms. These studies are referred to as double-zero event studies. The influence of double-zero event studies has been researched in the literature, but it remains unsettled. Some argued that in theory, these studies contain information for inference, whereas others do not observe their influence in numerical studies. This paper examines when and how double-zero event studies contribute to inference in Bayesian analysis. Through extensive numerical studies, we demonstrate that 1) Type I error can be significantly inflated, and 2) the testing power can be significantly decreased if double zeros event studies are excluded from the analysis.