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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. Working paper series / Department of Economics 219, University of Zurich.

Abstract

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.

Abstract

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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2 citations in Microsoft Academic

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Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Economics
Working Paper Series > Department of Economics
Dewey Decimal Classification:330 Economics
JEL Classification:C12
Uncontrolled Keywords:Adjusted p-values, multiple testing, resampling, stepdown procedure
Language:English
Date:February 2016
Deposited On:24 Feb 2016 14:38
Last Modified:02 Feb 2018 09:52
Series Name:Working paper series / Department of Economics
Number of Pages:6
ISSN:1664-7041
OA Status:Green
Official URL:http://www.econ.uzh.ch/static/wp/econwp219.pdf
Related URLs:http://www.econ.uzh.ch/static/workingpapers-new.php

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