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

Joseph P. Romano and Michael Wolf

No 219, ECON - Working Papers from Department of Economics - 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.

Keywords: Adjusted p-values; multiple testing; resampling; stepdown procedure (search for similar items in EconPapers)
JEL-codes: C12 (search for similar items in EconPapers)
Date: 2016-02
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 (205)

Downloads: (external link)
https://www.zora.uzh.ch/id/eprint/123047/1/econwp219.pdf (application/pdf)

Related works:
Journal Article: Efficient computation of adjusted p-values for resampling-based stepdown multiple testing (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zur:econwp:219

Access Statistics for this paper

More papers in ECON - Working Papers from Department of Economics - University of Zurich Contact information at EDIRC.
Bibliographic data for series maintained by Severin Oswald ().