JSM 2004 - Toronto

Abstract #300322

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Activity Number: 423
Type: Topic Contributed
Date/Time: Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300322
Title: Maximum Likelihood Estimation for the Number of True Null Hypotheses in a Multiple Two-sided Hypotheses-testing Problem
Author(s): Huey-Miin Hsueh*+
Companies: National Cheng-Chi University
Address: 64, Sec. 2, Zhi-Nan Rd., Taipei, International, 116, Taiwan
Keywords: maximum likelihood estimation ; multiple testing ; power ; Type I error rate
Abstract:

When there are many hypotheses to be tested, the risk of false positive finding in the simultaneous inference severely increases. A multiple comparison procedure (MCP), which uses a conservative adjustment in significance level of each test, is suggested for well-controlled familywise Type I error rate(FEW). However, the conservativeness of a MCP becomes substantial as the number of hypotheses increases. If the number of true null hypotheses, m0, is known, it can be used to improve the power for a MCP. In a multiple two-sided hypotheses testing problem, two types of maximum likelihood estimator (MLE) for m0, which is based on the relationship between per-comparison-wise Type I error rate (CWE) and power of each hypothesis testing procedure, will be introduced in this talk. Through intensive simulation studies, the MLE is found to have satisfactory performance and is comparable to the existent preferred method. The analysis of a real dataset from a microarray experiment is given as an illustration.

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