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.

引用

页码：38 / 40

页数：3

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