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


Romano, Joseph P; Wolf, Michael (2016). Efficient computation of adjusted p-values for resampling-based stepdown multiple testing. Statistics and Probability Letters, 113:38-40.

Abstract

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.

Abstract

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Uncontrolled Keywords:Adjusted p-values, multiple testing, resampling, stepdown procedure
Language:English
Date:March 2016
Deposited On:30 Mar 2016 07:48
Last Modified:24 Sep 2019 21:50
Publisher:Elsevier
ISSN:0167-7152
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.spl.2016.02.012
Related URLs:https://www.zora.uzh.ch/123047/

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