Comparison of Bayesian and Frequentist Multiplicity Correction For Testing Mutually Exclusive Hypotheses Under Data Dependence

2016/11/17 by Sean Chang, James O. Berger, Chang, Sean +1
Mathematics · #Advanced Statistical Methods and Models #FOS: Mathematics #Statistical Methods and Inference #Statistical Methods in Clinical Trials #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.1611.05909

openalex publication_date 2016/11/17 · openalex created_date 2016/11/30 · openalex updated_date 2026/07/28

Abstract

The problem of testing mutually exclusive hypotheses with dependent test statistics is considered. Bayesian and frequentist approaches to multiplicity control are studied and compared to help gain understanding as to the effect of test statistic dependence on each approach. The Bayesian approach is shown to have excellent frequentist properties and is argued to be the most effective way of obtaining frequentist multiplicity control, without sacrificing power, when there is considerable test statistic dependence.

Citations

• Adapting to unknown sparsity by controlling the false discovery rate

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