An informed reference prior for between-study heterogeneity in meta-analyses of binary outcomes
An informed reference prior for between-study heterogeneity in meta-analyses of binary outcomes
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DOI：
10.1002/sim.4326
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发表时间：
2011-11-20
影响因子：
2
通讯作者：
Pullenayegum, Eleanor M.
中科院分区：
文献类型：
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作者：
Pullenayegum, Eleanor M.
众所周知，当贝叶斯荟萃分析包含少量研究时，推断可能会对研究间方差的先验选择敏感。选择模糊先验并不能解决问题，因为根据模糊程度，推论可能会有很大不同。此外，由于数据提供的有关研究间异质性的信息很少，因此基于模糊先验的研究间方差的后验推断往往是不现实的。因此，最好对研究间方差采用合理的、知情的先验。然而，人们对现实分布的构成知之甚少。基于 Cochrane 系统评价数据库的数据，本文描述了已发表的荟萃分析中研究间方差的分布，并提出了一些现实的、知情的先验，用于二元结果的荟萃分析。希望这些先验能够改善贝叶斯荟萃分析推论的校准。版权所有 (C) 2011 John Wiley & Sons, Ltd.
It is well known that when a Bayesian meta-analysis includes a small number of studies, inference can be sensitive to the choice of prior for the between-study variance. Choosing a vague prior does not solve the problem, as inferences can be substantially different depending on the degree of vagueness. Moreover, because the data provide little information on between-study heterogeneity, posterior inferences for the between-study variance based on vague priors will tend to be unrealistic. It is thus preferable to adopt a reasonable, informed prior for the between-study variance. However, relatively little is known about what constitutes a realistic distribution. On the basis of data from the Cochrane Database of Systematic Reviews, this paper describes the distribution of between-study variance in published meta-analyses, and proposes some realistic, informed priors for use in meta-analyses of binary outcomes. It is hoped that these priors will improve the calibration of inferences from Bayesian meta-analyses. Copyright (C) 2011 John Wiley & Sons, Ltd.