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Activity Number: 604
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract #319340
Title: Quick Multiple Monte Carlo Testing
Author(s): Georg Hahn* and Axel Gandy
Companies: Imperial College London and Imperial College London
Keywords: multiple testing ; Bonferroni ; p value ; Benjamini Hochberg ; Monte Carlo ; Thompson Sampling
Abstract:

Multiple hypothesis testing is widely used to evaluate scientific studies involving statistical tests. However, for many of these tests, p-values are not available and are thus often approximated using Monte Carlo tests such as permutation tests or bootstrap tests. This talk presents a simple algorithm based on Thompson Sampling to test multiple hypotheses. It works with arbitrary multiple testing procedures, in particular with step-up and step-down procedures. Its main feature is to sequentially allocate Monte Carlo effort, generating more Monte Carlo samples for tests whose decisions are so far less certain. A simulation study demonstrates that for a low computational effort, the new approach yields a higher power and a higher degree of reproducibility of its results than previously suggested methods.


Authors who are presenting talks have a * after their name.

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