Arbeitspapier
Multiple testing of one-sided hypotheses: Combining Bonferroni and the bootstrap
In many multiple testing problems, the individual null hypotheses (i) concern univariate parameters and (ii) are one-sided. In such problems, power gains can be obtained for bootstrap multiple testing procedures in scenarios where some of the parameters are "deep in the null" by making certain adjustments to the null distribution under which to resample. In this paper, we compare a Bonferroni adjustment that is based on finite-sample considerations with certain "asymptotic" adjustments previously suggested in the literature.
- Sprache
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Englisch
- Erschienen in
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Series: Working Paper ; No. 254
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
- Thema
-
Bonferroni
multiple hypothesis testing
stepwise method
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Romano, Joseph P.
Wolf, Michael
- Ereignis
-
Veröffentlichung
- (wer)
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University of Zurich, Department of Economics
- (wo)
-
Zurich
- (wann)
-
2017
- DOI
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doi:10.5167/uzh-138641
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Romano, Joseph P.
- Wolf, Michael
- University of Zurich, Department of Economics
Entstanden
- 2017