JSM 2005 Online Program

Abstract #303031

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.

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Activity Number:	201
Type:	Invited
Date/Time:	Monday, August 8, 2005 : 4:00 PM to 5:50 PM
Sponsor:	ASA
Abstract - #303031
Title:	A Bayes/Frequentist Roadmap
Author(s):	Roderick J. Little*+
Companies:	University of Michigan
Address:	Dept. of Biostatistics, Ann Arbor, MI, 48109,
Keywords:	Bayesian statistics ; calibrated Bayes ; frequentist statistics ; model diagnostics ; statistical modeling
Abstract:	The lack of an agreed inferential basis for statistics makes life "interesting" for academic statisticians, but at the price of negative implications for the practice and status of statistics in industry, science, and government. Our discipline will only mature when we come to a basic agreement about how to apply statistics to real problems. Some illustrations and implications of the existing Bayes/frequentist rift, specific and general, are offered, including survey inference and missing data. Strengths and weaknesses of the frequentist and Bayes paradigms are outlined. Can the rift be breached? In the talk, a roadmap for a possible frequentist/Bayes compromise is outlined based on the work of Box, Rubin, and others. The compromise is sometimes called "calibrated Bayes," and asserts that inferences should be Bayesian and model-based, but model formation and assessment can and should involve frequentist ideas. Some implications of this proposed compromise for the future teaching and practice of statistics are offered.

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