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Activity Number: 381 - Recent Advances in Multiple Testing and False Discovery Rate Analysis
Type: Invited
Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract #300546 Presentation
Title: Adapting to One- and Two-Way Classified Structures of Hypotheses While Controlling False Discoveries
Author(s): Sanat K Sarkar*
Companies: Temple University
Keywords: Multiple Testing ; One-Way Classifioed Hypotheses; Two-Way Classified Hypotheses; False Discovery Rate; Local False Discovery Rate

Modern scientific investigations, notably in genome-wide association and neuroimaging studies, often give rise to multiple testing problems for hypotheses that are classified according to multiple criteria. This creates a situation where the significance of a hypothesis needs to be carefully assessed by taking into account the underlying classification structure. We refer to a set of hypotheses as one-way classified hypotheses if they are classified according to one criterion, and as two-way classified hypotheses if they are classified according to two different criteria. This talk presents some newer results on controlling false discoveries while testing multiple hypotheses that appear in one-way and two-way classified forms.

Authors who are presenting talks have a * after their name.

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