文章基本信息

标题：A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control
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作者：Luis Gutiérrez ; Andrés F. Barrientos ; Jorge González 等
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2019
卷号：14
期号：2
页码：649-675
DOI：10.1214/18-BA1122
语种：English
出版社：International Society for Bayesian Analysis
摘要：We propose a Bayesian nonparametric strategy to test for differences between a control group and several treatment regimes. Most of the existing tests for this type of comparison are based on the differences between location parameters. In contrast, our approach identifies differences across the entire distribution, avoids strong modeling assumptions over the distributions for each treatment, and accounts for multiple testing through the prior distribution on the space of hypotheses. The proposal is compared to other commonly used hypothesis testing procedures under simulated scenarios. Two real applications are also analyzed with the proposed methodology.
关键词：Bayes factor; Dependent Dirichlet process; spike and slab priors; shift function.