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Meta-analysis framework for exact inferences with application to the analysis of rare events

Author(s): Guang Yang, Dungang Liu, Junyuan Wang, Min-ge Xie

Status: Published
Year: 2016
Publication Name: Biometrics
Volume: 72, Issue: 4, Page Number(s): 1378–1386


Abstract

The usefulness of meta-analysis has been recognized in the evaluation of drug safety, as a single trial usually yields few adverse events and offers limited information. For rare events, conventional meta-analysis methods may yield an invalid inference, as they often rely on large sample theories and require empirical corrections for zero events. These problems motivate research in developing exact methods, including Tian et al.'s method of combining confidence intervals (2009, Biostatistics, 10, 275–281) and Liu et al.'s method of combining p-value functions (2014, JASA, 109, 1450–1465). This article shows that these two exact methods can be unified under the framework of combining confidence distributions (CDs). Furthermore, we show that the CD method generalizes Tian et al.'s method in several aspects. Given that the CD framework also subsumes the Mantel–Haenszel and Peto methods, we conclude that the CD method offers a general framework for meta-analysis of rare events. We illustrate the CD framework using two real data sets collected for the safety analysis of diabetes drugs.


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