Multiple testing procedures under confounding

dc.creatorGhosh, Debashis
dc.date2008-05-15
dc.date.accessioned2026-07-07T12:18:56Z
dc.date.available2026-07-07T12:18:56Z
dc.descriptionWhile multiple testing procedures have been the focus of much statistical research, an important facet of the problem is how to deal with possible confounding. Procedures have been developed by authors in genetics and statistics. In this chapter, we relate these proposals. We propose two new multiple testing approaches within this framework. The first combines sensitivity analysis methods with false discovery rate estimation procedures. The second involves construction of shrinkage estimators that utilize the mixture model for multiple testing. The procedures are illustrated with applications to a gene expression profiling experiment in prostate cancer.
dc.descriptionPublished in at http://dx.doi.org/10.1214/193940307000000176 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0805.2328
dc.identifierhttp://arxiv.org/abs/0805.2328
dc.identifierIMS Collections 2008, Vol. 1, 243-256
dc.identifierdoi:10.1214/193940307000000176
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212585
dc.subjectMethodology
dc.subjectStatistics Theory
dc.subject62P10 (Primary) 92D10 (Secondary)
dc.titleMultiple testing procedures under confounding
dc.typetext

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