p-Value Adjustments for Asymptotic Control of the Generalized Familywise Error Rate

Christopher Bennett ()
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Christopher Bennett: Department of Economics, Vanderbilt University

No 905, Vanderbilt University Department of Economics Working Papers from Vanderbilt University Department of Economics

Abstract: This paper introduces a computationally efficient bootstrap procedure for obtaining multiplicity-adjusted p-values in situations where multiple hypotheses are tested simultaneously. This new testing procedure accounts for the mutual dependence of the individual statistics, and is shown under weak conditions to maintain asymptotic control of the generalized familywise error rate. Moreover, the estimated critical values (p-values) obtained via our procedure are less sensitive to the inclusion of true hypotheses and, as a result, our test has greater power to identify false hypotheses even as the collection of hypotheses under test increases in size. Another attractive feature of our test is that it leads naturally to balance among the individual hypotheses under test. This feature is especially attractive in settings where balance is desired but alternative approaches, such as those based on studentization, are difficult or infeasible.

Keywords: Bootstrap; familywise error; multiple testing; step-down; balanced testing (search for similar items in EconPapers)
JEL-codes: C12 C14 C52 (search for similar items in EconPapers)
Date: 2009-04
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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http://www.accessecon.com/pubs/VUECON/vu09-w05.pdf First version, 2009 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:van:wpaper:0905

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