Optimal weighting for false discovery rate control

被引：41
|
作者：
Roquain, Etienne [1 ]
van de Wiel, Mark A. [2 ]
机构：
[1] Univ Paris 06, LPMA, F-75252 Paris 05, France
[2] Vrije Univ Amsterdam, Med Ctr, NL-1007 MB Amsterdam, Netherlands
来源：
ELECTRONIC JOURNAL OF STATISTICS | 2009年 / 3卷
关键词：
False discovery rate; multiple testing; p-value weighting; power maximization; DEPENDENCE;
D O I：
10.1214/09-EJS430
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
How to weigh the Benjamini-Hochberg procedure? In the context of multiple hypothesis testing, we propose a new step-wise procedure that controls the false discovery rate (FDR) and we prove it to be more powerful than any weighted Benjamini-Hochberg procedure. Both finite sample and asymptotic results are presented. Moreover, we illustrate good performance of our procedure in simulations and a genomics application. This work is particularly useful in the case of heterogeneous p-value distributions.
引用
收藏
页码：678 / 711
页数：34
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