Meta-analysis of rare event data has recently received increasing attention due to the challenging issues rare events pose to traditional meta-analytic methods. One specific way to combine information and analyze rare event meta-analysis data utilizes confidence distributions (CDs). While several CD methods exist, no comparisons have been made to determine which method is best suited for homogeneous or heterogeneous meta-analyses with rare events. In this article, we review several CD methods: Fisher's classic P-value combination method, one that combines P-value functions, another that combines confidence intervals, and one that combines confidence log-likelihood functions. We compare these CD approaches, and we propose and compare variations of these methods to determine which method produces reliable results for homogeneous or heterogeneous rare event meta-analyses. We find that for homogeneous rare event data, most CD methods perform very well. On the other hand, for heterogeneous rare event data, there is a clear split in performance between some CD methods, with some performing very poorly and others performing reasonably well.

中文翻译：

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罕见事件荟萃分析的置信度分布方法比较

由于罕见事件对传统元分析方法构成的挑战性问题，罕见事件数据的元分析最近受到越来越多的关注。一种结合信息和分析罕见事件元分析数据的特定方法是利用置信度分布 (CD)。虽然存在几种 CD 方法，但尚未进行比较以确定哪种方法最适合具有罕见事件的同质或异质荟萃分析。在本文中，我们回顾了几种 CD 方法：Fisher 的经典P值组合方法，一种将P-value 函数，另一个结合了置信区间，一个结合了置信对数似然函数。我们比较了这些 CD 方法，我们提出并比较了这些方法的变体，以确定哪种方法为同质或异质罕见事件荟萃分析产生可靠的结果。我们发现，对于同质的罕见事件数据，大多数 CD 方法表现非常好。另一方面，对于异构稀有事件数据，一些 CD 方法之间的性能存在明显差异，一些性能非常差，而另一些性能相当好。