ASYMPTOTIC OPTIMALITY OF THE WESTFALL-YOUNG PERMUTATION PROCEDURE FOR MULTIPLE TESTING UNDER DEPENDENCE

• 成果类型: Article
• 署名作者: Meinshausen, Nicolai; Maathuis, Marloes H.; Buehlmann, Peter
• 署名单位: University of Oxford; Swiss Federal Institutes of Technology Domain; ETH Zurich
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/11-AOS946
• 发表日期: 2011
• 页码: 3369-3391
• 关键词: false discovery rate; genome-wide association; HIGHER CRITICISM; gene

摘要

Test statistics are often strongly dependent in large-scale multiple testing applications. Most corrections for multiplicity are unduly conservative for correlated test statistics, resulting in a loss of power to detect true positives. We show that the Westfall-Young permutation method has asymptotically optimal power for a broad class of testing problems with a block-dependence and sparsity structure among the tests, when the number of tests tends to infinity.