Statistical properties of an early stopping rule for resampling-based multiple testing

被引:18
|
作者
Jiang, Hui [1 ]
Salzman, Julia [2 ]
机构
[1] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
[2] Stanford Univ, Dept Stat, Stanford, CA 94305 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Bootstrap; Early stopping; False discovery rate control; Multiple hypothesis testing; Resampling; FALSE DISCOVERY RATE; BONFERRONI PROCEDURE; BOOTSTRAP; INTERVALS; NUMBER;
D O I
10.1093/biomet/ass051
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Resampling-based methods for multiple hypothesis testing often lead to long run times when the number of tests is large. This paper presents a simple rule that substantially reduces computation by allowing resampling to terminate early on a subset of tests. We prove that the method has a low probability of obtaining a set of rejected hypotheses different from those rejected without early stopping, and obtain error bounds for multiple hypothesis testing. Simulation shows that our approach saves more computation than other available procedures.
引用
收藏
页码:973 / 980
页数:8
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