Greetings, and apologies for cross-posting.
If you would please make the following announcement known to any of your
colleagues, students, etc., who may be interested, that would be terrific.
Many thanks and best wishes, David Draper
2004 American Statistical Association LearnSTAT Program Offering:
Title: Intermediate/Advanced Bayesian Hierarchical Modeling
Date: 26 March 2004
Instructor: David Draper
Department of Applied Mathematics and Statistics
University of California, Santa Cruz
Summary: An award-winning short course on intermediate- and
advanced-level methods and applications of Bayesian hierarchical
modeling, including (a) reviews of Bayesian modeling, Bayesian
computation, and hierarchical models (HMs) for meta-analysis, and (b)
coverage of (1) Bayesian model diagnostics, model checking, and model
elaboration; (2) mixture modeling with latent variables; (3) HMs for
clustered (hierarchical, multilevel) data; and (4) semi-parametric HMs
for dealing realistically with model uncertainty. Case studies drawn from
medicine, education, and environmental risk assessment.
One-day course: 6 hours of material covered in an 8-hour time slot, with
30 minutes of breaks in each of the morning and afternoon sessions and a
one-hour break for lunch
Location: Arlington Campus Professional Center
George Mason University
3401 North Fairfax Drive
Arlington, Virginia
(Near Washington, DC)
Registration Fee: $500 for ASA members
$600 for nonmembers
(Registration fee includes 225 pages of materials, lunch, and
refreshments for AM and PM breaks)
Registration Deadline: March 5, 2004
Register Online at: www.amstat.org/education
Abstract:
This course provides coverage of intermediate- and advanced-level topics
arising in the formulation, fitting, and checking of hierarchical or
multilevel models from the Bayesian point of view. The Bayesian approach
is particularly effective in fitting hierarchical models because other
model-based methods -- principally involving maximum likelihood -- often
do not capture all relevant sources of uncertainty, leading to
over-confident decisions and scientific conclusions.
The basic principles of Bayesian hierarchical modeling are reviewed in
this course with emphasis on practical rather than theoretical issues.
Intermediate- and advanced-level ideas are illustrated with real data
drawn from case studies involving complicated applications of
hierarchical models in cluster sampling and mixture modeling. The course
is intended for applied statisticians with an interest in learning more
about intermediate and advanced topics in hierarchical modeling in
general, and the Bayesian analysis of such models in particular.
Instructor:
David Draper is a Professor in, and Chair of, the Department of Applied
Mathematics and Statistics in the Baskin School of Engineering at the
University of California, Santa Cruz. From 2001 to 2003 he served as the
President-Elect, President, and Past President of the International
Society for Bayesian Analysis (ISBA). His research is in the areas of
Bayesian inference and prediction, model uncertainty and empirical
model-building, hierarchical modeling, Markov Chain Monte Carlo methods,
and Bayesian semi-parametric methods, with applications mainly in health
policy, education, and environmental risk assessment. When he gave this
same short course at the San Francisco JSM last year, it won the ASA
Excellence in Continuing Education award for 2003. He has received or
been nominated for major teaching awards everywhere he has taught
(University of Chicago; RAND Graduate School of Public Policy; University
of California, Los Angeles; University of Bath (U.K.); and University of
California, Santa Cruz). He has a particular interest in the exposition
of complex statistical methods and ideas in the context of real-world
applications.
For more information and to register for this course, visit the Education
section of the ASA Web site at www.amstat.org/education and click on the
link for this course.
Questions? email [log in to unmask] or call (703) 684-1221 ext. 166.
=========================================================================
Professor David Draper
Chair, Department of
Applied Mathematics email [log in to unmask]
and Statistics web http://www.ams.ucsc.edu/~draper/
Baskin School of phone (+1) (831) 459 1295
Engineering fax (+1) (831) 459 4829
University of California
1156 High Street departmental web pages www.ams.ucsc.edu
Santa Cruz CA 95064 USA
Interesting quotes, number 24 in a series:
The end is in the beginning; and yet you go on.
-- Samuel Beckett
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