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Volume 24 (2024)
Volume 24, Issue 3 (In progress)
Pg 399 - 526 (November 2024)
Volume 24, Issue 2
Pg 197 - 397 (July 2024)
Volume 24, Issue 1
Pg 1 - 196 (March 2024)
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JP Journal of Biostatistics
JP Journal of Biostatistics
Volume 4, Issue 2, Pages 181 - 201 (June 2010)
TESTING MULTIPLE HYPOTHESES USING POPULATION INFORMATION OF SAMPLES
Mingqi Wu and Faming Liang
Abstract:
Multiple hypothesis tests have been widely studied in the recent literature of statistics, however, most of the studies focus on how to control the false discovery rate for a given set of test scores or, equivalently, test p-values. Given the vast data involved in a multiple hypothesis test, it is natural to think about how to make use of population information of samples to improve the power of the test for each individual subject and thus to improve the power of the multiple hypothesis test. In this paper, we propose a nonparametric method for evaluation of test scores for each individual subject involved in a multiple hypothesis test. The method consists of two key steps, smoothing over neighboring subjects and density estimation over control samples, both of which allow for the use of population information of the subjects. The new method is tested on both the ChIP-chip data and the microarray data. The numerical results indicate that use of population information can significantly improve the power of multiple hypothesis tests.
Keywords and phrases:
ChIP-chip, density estimation, false discovery rate, microarray, multiple hypothesis testing, smoothing.
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P-ISSN: 0973-5143
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