JSM 2005 Online Program

Abstract #302475

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Legend:

= Applied Session,

= Theme Session,

= Presenter

Activity Number:	341
Type:	Invited
Date/Time:	Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor:	IMS
Abstract - #302475
Title:	Bayesian and Frequentist Approaches to Multiple Testing
Author(s):	M. J. Bayarri*+ and James Berger
Companies:	University of Valencia and Duke University
Address:	Department of Statistics and O.R., Burjassot, 46100, Spain
Keywords:	Bayesian Model selection ; Decision theory ; false discovery rate ; multiplicity
Abstract:	Recently, with large screening problems (such as gene expression problems), there has been a renewed interest in investigating alternatives to adjust for multiple hypothesis testing. While "no adjustment" is considered too liberal, the classic adjustment for familywise error rate is perceived as resulting in too conservative adjustments. More recent proposals control instead the "false discovery rate" or related (frequentist, Bayesian, and eclectic) quantities. In this paper, we review these proposals and investigate whether they play a role in the unification of Bayesian/frequentist approaches. As a basis for comparison, a full Bayesian analysis of multiple testing is presented in a special case, with the focus being on the way in which the Bayesian methodology automatically "adjusts" for multiplicity.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2005 program