Designing Monte Carlo Implementations of Permutation or Bootstrap Hypothesis Tests

DOI10.1198/000313002753631385zbMath1182.62094OpenAlexW2034669660WikidataQ56940801 ScholiaQ56940801MaRDI QIDQ5189901

Dean A. Follmann, Michael P. Fay

Publication date: 11 March 2010

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/000313002753631385

zbMATH Keywords

simulationresamplingsequential designresample size

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Nonparametric statistical resampling methods (62G09) Monte Carlo methods (65C05) Sequential statistical analysis (62L10)

Related Items (7)

Confidence intervals for spatial scan statistic ⋮ Truncated sequential Monte Carlo test with exact power ⋮ Confidence interval for the bootstrapP-value and sample size calculation of the bootstrap test ⋮ On the expected runtime of multiple testing algorithms with bounded error ⋮ A simple method for implementing Monte Carlo tests ⋮ Bounding the resampling risk for sequential Monte Carlo implementation of hypothesis tests ⋮ Optimal allocation of Monte Carlo simulations to multiple hypothesis tests

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