The ASA Bay
Area Chapter announces an applied statistics workshop to be held on June 4 and
5, 2008 at the Clarion Hotel, San Francisco Airport. Details about the
seminar and the registration form are attached. Please plan to register for the
workshop at an early date, as space is limited.
Topic:
Linear Mixed
and Generalized Linear Mixed Models
Dates
and Time:
8:00 am - 4:30
pm on Wednesday and/Thursday, June 4/5, 2008
Location:
Clarion Hotel SFO,
401 E. Millbrae Avenue, Millbrae, CA 94030
Instructor:
Charles E.
McCulloch
Division of
Biostatistics, Department of Epidemiology and Biostatistics
University of
California, San Francisco
Description:
The class of
generalized linear mixed models (GLMMs) is a broad class of statistical models
generalizing both linear mixed models (LMMs) and generalized linear models (GLMs). As such it is capable of
accommodating nonlinear responses, correlated data and non-normal
distributions. This makes it quite useful in practice. For example,
GLMMs give a natural way to specify a correlated data model for binary data.
The workshop
will briefly review the concepts of linear mixed models and the use of random effects as well as the modeling
strategy behind generalized linear models. From these two classes of
models will be developed generalized linear mixed models. A series of
examples will be considered to develop intuition about how to specify these
models in real situations.
Next, features
of generalized linear mixed models will be developed and strategies for fitting
the models to data will be described and contrasted with approaches such as
generalized estimating equations. A series of case studies will be used
to illustrate the practical use of these models. The focus in the course
will be on approaches to modeling, methods of estimation and inference, and
available software.
Biographical
Sketch of the Instructor:
Professor
Chuck McCulloch received his PhD in Statistics from Cornell University and is
currently Professor and Head of the Division of Biostatistics at the University
of California, San Francisco. Before going to UCSF, he was on the faculty at
Florida State University and Cornell University. He spent 18 years at
Cornell where he was the founding Chair of the Department of Statistical
Science. He conducts research in the areas of longitudinal data analysis,
generalized linear mixed models, and latent class models. He is the author of
numerous scientific publications and is the co-author of three textbooks:
An Introduction to Generalized Linear Mixed Models (Wiley), Variance
Components (Wiley), and Regression Methods in Biostatistics: Linear, Logistic,
Survival, and Repeated Measures Models (Springer). In addition, Dr McCulloch is
the author of the Institute of Mathematical Statistics monograph,
"Generalized Linear Mixed Models." He is a fellow of the
American Statistical Association and an elected member of the International
Statistical Institute. He has over 25 years of statistical consulting
experience.
Dr. McCulloch
has taught numerous short courses on generalized linear mixed models, including
one in 2005 at the 61st Annual Deming Conference on Applied Statistics.
He was the primary lecturer for an NSF-CBMS Regional Research Conference
in 1999 on the topic of generalized linear mixed models.
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