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June 2019 A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control
Luis Gutiérrez, Andrés F. Barrientos, Jorge González, Daniel Taylor-Rodríguez
Bayesian Anal. 14(2): 649-675 (June 2019). DOI: 10.1214/18-BA1122

Abstract

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.

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Luis Gutiérrez. Andrés F. Barrientos. Jorge González. Daniel Taylor-Rodríguez. "A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control." Bayesian Anal. 14 (2) 649 - 675, June 2019. https://doi.org/10.1214/18-BA1122

Information

Published: June 2019
First available in Project Euclid: 18 September 2018

zbMATH: 07089621
MathSciNet: MR3959876
Digital Object Identifier: 10.1214/18-BA1122

Subjects:
Primary: 62G07 , 62G10
Secondary: 62G05

Keywords: Bayes factor , dependent Dirichlet process , shift function , spike and slab priors

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Vol.14 • No. 2 • June 2019
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