论文标题
使用经典方法和架子比较先前的启发聚集
A Comparison of Prior Elicitation Aggregation using the Classical Method and SHELF
论文作者
论文摘要
从专家提出的主观贝叶斯先前的分布可以汇总在一起以组成小组先验。本文使用针对临床试验进行的专家启发，将相互重量聚集，经典方法和谢菲尔德启发框架形成的汇总先验与彼此和个人专家先验进行了比较。使用适当的评分规则比较了聚合方法和个人专家先验分布，以比较分布的信息性和校准。这三种聚合方法的表现优于个人专家，而谢菲尔德的启发框架在其中表现最好。
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 amongst them.
