Efficient computation of adjusted p-values for resampling-based stepdown multiple testing

被引：156
|
作者：
Romano, Joseph P. [1 ]
Wolf, Michael [2 ]
机构：
[1] Stanford Univ, Dept Econ & Stat, Stanford, CA 94305 USA
[2] Univ Zurich, Dept Econ, CH-8032 Zurich, Switzerland
来源：
STATISTICS & PROBABILITY LETTERS | 2016年 / 113卷
基金：
美国国家科学基金会;
关键词：
Adjusted p-values; Multiple testing; Resampling; Stepdown procedure;
D O I：
10.1016/j.spl.2016.02.012
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：
There has been a recent interest in reporting p-values adjusted for the resampling-based stepdown multiple testing procedures proposed in Romano and Wolf (2005a,b). The original papers only describe how to carry out multiple testing at a fixed significance level. Computing adjusted p-values instead in an efficient manner is not entirely trivial. Therefore, this paper fills an apparent gap by detailing such an algorithm. (C) 2016 Elsevier B.V. All rights reserved.
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页码：38 / 40
页数：3
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