- Bayesian Anal.
- Volume 14, Number 2 (2019), 649-675.
A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control
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.
Bayesian Anal., Volume 14, Number 2 (2019), 649-675.
First available in Project Euclid: 18 September 2018
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Gutiérrez, Luis; Barrientos, Andrés F.; González, Jorge; Taylor-Rodríguez, Daniel. A Bayesian Nonparametric Multiple Testing Procedure for Comparing Several Treatments Against a Control. Bayesian Anal. 14 (2019), no. 2, 649--675. doi:10.1214/18-BA1122. https://projecteuclid.org/euclid.ba/1537258138
- Supplementary Material for ‘A Bayesian nonparametric multiple testing procedure for comparing several treatments against a control’. The online Supplementary Material contains the Gibbs Algorithm described in Section 3.4, as well as the image plots of the comparison between our proposal and other classical hypothesis tests (Section 4.2), including both multiple and two-sample cases.