Abstract Details
Activity Number:
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35
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Type:
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Contributed
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Date/Time:
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Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #309515 |
Title:
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Testing Multiple Biological Mediators Simultaneously
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Author(s):
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Simina Boca*+ and Rashmi Sinha and Amanda J. Cross and Steven C. Moore and Joshua Sampson
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Companies:
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National Cancer Institute and National Cancer Institute and National Cancer Institute and National Cancer Institute and DCEG, National Cancer Institute
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Keywords:
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mediation ;
multiple testing ;
family wise error rate ;
permutation test
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Abstract:
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Numerous statistical methods adjust for "multiple comparisons" when testing whether multiple biomarkers, such as hundreds or thousands of gene expression or metabolite levels, are directly associated with an outcome. However, other than the simple Bonferroni correction, there are no adjustment methods for testing whether multiple biomarkers are biological mediators between a known risk factor and a disease. We propose a novel double permutation approach which controls the Family Wise Error Rate (FWER) when testing multiple mediators. We show, via simulations, that unlike testing multiple associations, the appropriate permutation test can offer a substantial gain in power over the simpler Bonferroni approach. We apply our permutation test to a case/control study of dietary risk factors and colorectal adenoma, to show that docosahexaenoate is a likely mediator between fish consumption and decreased colorectal adenoma risk.
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Authors who are presenting talks have a * after their name.
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