Subjective Bayesian prior distributions elicited from experts can be aggregated together to form group priors. This paper compares aggregated priors formed by equal weight aggregation, the classical method and the Sheffield elicitation framework to each other and individual expert priors, using an expert elicitation carried out for a clinical trial. Aggregation methods and individual expert prior distributions are compared using proper scoring rules to compare the informativeness and calibration of the distributions. The three aggregation methods outperform the individual experts, and the Sheffield elicitation framework performs best among them.

中文翻译：

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使用经典方法和 SHELF 的先验诱导聚合的比较

从专家那里得到的主观贝叶斯先验分布可以聚合在一起形成组先验。本文使用为临床试验进行的专家引出，比较了由等权重聚合、经典方法和谢菲尔德引出框架形成的聚合先验相互和个人专家先验。使用适当的评分规则比较聚合方法和个人专家先验分布，以比较分布的信息量和校准。三种聚合方法均优于个别专家，其中谢菲尔德启发框架表现最佳。