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A Bayesian Approach to the Multiple Comparisons Problem
Journal article   Open access

A Bayesian Approach to the Multiple Comparisons Problem

Andrew A Neath and Joseph E Cavanaugh
Journal of data science, Vol.4(2), pp.131-146
07/13/2021
DOI: 10.6339/JDS.2006.04(2).266
url
https://doi.org/10.6339/JDS.2006.04(2).266View
Published (Version of record) Open Access

Abstract

Consider the problem of selecting independent samples from several populations for the purpose of between-group comparisons. An important aspect of the solution is the determination of clusters where mean levels are equal, often accomplished using multiple comparisons testing. We formulate the hypothesis testing problem of determining equal-mean clusters as a model selection problem. Information from all competing models is combined through Bayesian methods in an effort to provide a more realistic accounting of uncertainty. An example illustrates how the Bayesian approach leads to a logically sound presentation of multiple comparison results.

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