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Activity Number: 185 - Contributed Poster Presentations: IMS
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #302871
Title: Multiple Hypothesis Testing with Discrete Data: Minimally Discrete P-Values
Author(s): Joshua Habiger*
Companies: Oklahoma State University
Keywords: Discrete Data; False Discovery Rate; Multiple Testing; p-value

When testing a null hypothesis with discrete data the natural p-value is conservative, the mid-p-value can be liberal and the randomized p-value is more variable. This work show that this unavoidable ``discreteness effect'' is exacerbated when testing multiple null hypotheses with discrete data. A new ``minimally discrete'' (MD) testing procedure and p-value are developed and shown to dominate traditional approaches for handling the discreteness in that the MD natural p-value is less conservative while the MD randomized p-value is less variable. It is demonstrated that the MD p-values scale up well to high dimensional multiple testing.

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

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