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Open Access Bayesian evaluation of informative hypotheses for multiple populations

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This article is Open Access under the terms of the Creative Commons CC BY-NC-ND licence.

The software package Bain can be used for the evaluation of informative hypotheses with respect to the parameters of a wide range of statistical models. For pairs of hypotheses the support in the data is quantified using the approximate adjusted fractional Bayes factor (BF). Currently, the data have to come from one population or have to consist of samples of equal size obtained from multiple populations. If samples of unequal size are obtained from multiple populations, the BF can be shown to be inconsistent. This paper examines how the approach implemented in Bain can be generalized such that multiple‐population data can properly be processed. The resulting multiple‐population approximate adjusted fractional Bayes factor is implemented in the R package Bain.
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Keywords: Bain; Bayes factor; informative hypotheses; multiple populations

Document Type: Research Article

Publication date: May 1, 2019

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