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

There has been a recent interest in reporting p-values adjusted for 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.

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Year of publication:	2016
Authors:	Romano, Joseph P. ; Wolf, Michael
Publisher:	Zurich : University of Zurich, Department of Economics
Subject:	Adjusted p-values \| Multiple testing \| Resampling \| Stepdown procedure

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Series:	Working Paper ; 219
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.5167/uzh-123047 [DOI] 848510135 [GVK] hdl:10419/162422 [Handle]
Classification:	C12 - Hypothesis Testing
Source:	EconStor

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011663178