Online Program Home
My Program

Abstract Details

Activity Number: 254 - Contributed Poster Presentations: Section on Bayesian Statistical Science
Type: Contributed
Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #307331
Title: Criteria for Bayesian Hypothesis Testing for Two and More Groups
Author(s): Victor Pena*
Companies: Baruch College (CUNY)
Keywords: Bayesian; Decision Theory; Hypotesis testing

We propose new criteria for prior choice in two-sample hypothesis tests and find classes of priors that satisfy them (and classes that don't). The criteria have a common starting point: a hypothetical situation where perfect knowledge about one of the groups is attained, while the data for the other group are assumed to be fixed. In such a scenario, the Bayes decision of the two-sample problem should "converge" to the Bayes decision of a one-sample test where we know the distribution of the group for which we gain perfect information. The first criterion is based on a limiting argument where the sample size of one of the groups grows to infinity, whereas the second criterion is based upon conditioning on the "true" value of the parameters. We find priors where the limiting argument and conditioning give rise to equivalent Bayes decisions under perfect knowledge, and cases where they give rise to different Bayes decisions. We show that, with some prior specifications, the limiting Bayes decisions are not compatible with any prior specification for the one-sample problem. Finally, we include preliminary results in extensions to more than 2 groups.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program