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arXiv · 1402.2706

QuickMMCTest - Quick Multiple Monte Carlo Testing

Axel Gandy·Georg Hahn
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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 article 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.

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Axel Gandy, Georg Hahn. 2014-02-12. QuickMMCTest - Quick Multiple Monte Carlo Testing. https://doi.org/10.1007/s11222-016-9656-z

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