文章基本信息

标题：Equivalence between the Posterior Distribution of the Likelihood Ratio and a p-value in an Invariant Frame
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作者：Isabelle Smith ; André Ferrari
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2014
卷号：9
期号：4
页码：939-962
DOI：10.1214/14-BA877
语种：English
出版社：International Society for Bayesian Analysis
摘要：The Posterior distribution of the Likelihood Ratio (PLR) is proposed by Dempster in 1973 for significance testing in the simple vs. composite hypothesis case. In this hypothesis test case, classical frequentist and Bayesian hypothesis tests are irreconcilable, as emphasized by Lindley’s paradox, Berger & Selke in 1987 and many others. However, Dempster shows that the PLR (with inner threshold 1) is equal to the frequentist p-value in the simple Gaussian case. In 1997, Aitkin extends this result by adding a nuisance parameter and showing its asymptotic validity under more general distributions. Here we extend the reconciliation between the PLR and a frequentist p-value for a finite sample, through a framework analogous to the Stein’s theorem frame in which a credible (Bayesian) domain is equal to a confidence (frequentist) domain.