An informed reference prior for between-study heterogeneity in meta-analyses of binary outcomes

被引:38
作者
Pullenayegum, Eleanor M. [1 ,2 ]
机构
[1] McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON, Canada
[2] St Josephs Healthcare Hamilton, Biostat Unit, Hamilton, ON L8N 4A6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
meta-analysis; bayesian; random effects; prior; CLUSTER RANDOMIZED-TRIALS; PRIOR DISTRIBUTIONS; VARIANCE PARAMETERS; HIERARCHICAL-MODELS; BAYESIAN METHODS; SIMULATION; WINBUGS;
D O I
10.1002/sim.4326
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:3082 / 3094
页数:13
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