Multiple testing procedures under confounding
Debashis Ghosh
Abstract
While 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.
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Primary Subjects: 62P10
Secondary Subjects: 92D10
Keywords: association studies; empirical null hypothesis; multiple comparisons; statistical genomics
Full-text: Open access
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Permanent link to this document: http://projecteuclid.org/euclid.imsc/1207058277
Digital Object Identifier: doi:10.1214/193940307000000176
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