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Activity Number: 546
Type: Contributed
Date/Time: Thursday, August 10, 2006 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #306491
Title: Optimality Results for the Bonferroni Method with Large m
Author(s): Yonggang Lu*+ and Peter Westfall
Companies: Texas Tech University and Texas Tech University
Address: MS2101 ISQS COBA, Lubbock, TX, 79409,
Keywords: multiple comparisons ; Bonferroni method ; asymptotic optimality ; loss function
Abstract:

Modern methods of multiple comparisons, particularly those based on controlling the false discovery rate, are lax relative to the Bonferroni method in their assignment of significances; they are relatively more lax as m, the number of tests, increases. We point out that this laxness is based on an assumption concerning the size of the loss due to Type I errors relative to loss due to Type II errors, and challenge the generality of this assumption, providing alternative types of loss function for which the Bonferroni method is asymptotically (as m8) optimal.

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