Bayesian nonparametric k-sample tests for censored and uncensored data

Yuhui Chen and Timothy E. Hanson

Computational Statistics & Data Analysis, 2014, vol. 71, issue C, 335-346

Abstract: Polya tree priors are random probability distributions that are easily centered at standard parametric families, such as the normal. As such, they provide a convenient avenue toward creating a parametric/nonparametric test statistic “blend” for the classic problem of testing whether data distributions are the same across several subpopulations. Test-statistics that are (empirical) Bayes factors constructed from independent Polya tree priors are proposed. The Polya tree centering distributions are Gaussian with parameters estimated from the data and the p-values are obtained through the permutation of group membership indicators. Generalizations to censored and multivariate data are provided. The conceptually simple test statistic fares surprisingly well against competitors in simulations.

Keywords: Behrens–Fisher problem; Log-rank test; ANOVA; MANOVA; Polya tree (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:71:y:2014:i:c:p:335-346

DOI: 10.1016/j.csda.2012.11.003

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