Evaluating Statistical Methods Using Plasmode Data Sets in the Age of Massive Public Databases: An Illustration Using False Discovery Rates

Open Access

Peer-reviewed

Research Article

Gary L. Gadbury,

Affiliations Department of Statistics, Kansas State University, Manhattan, Kansas, United States of America, Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, Missouri, United States of America, Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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Qinfang Xiang,

Affiliation Endo Pharmaceuticals, Chadds Ford, Pennsylvania, United States of America
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Lin Yang,

Affiliation Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, Missouri, United States of America
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Stephen Barnes,

Affiliations Department of Pharmacology and Toxicology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America, Center for Nutrient–Gene Interaction, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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Grier P. Page,

Affiliation Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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David B. Allison

* E-mail: dallison@ms.soph.uab.edu

Affiliations Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America, Clinical Nutrition Research Center, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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Statistical data
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Gene expression
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Drug discovery
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