JSM Preliminary Online Program
This is the preliminary program for the 2006 Joint Statistical Meetings in Seattle, Washington.

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


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Legend: = Applied Session, = Theme Session, = Presenter, Sheraton Seattle Hotel & Towers = “S”
Washington State Convention & Trade Center = “CC”, Grand Hyatt Seattle = “H”

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CE_20C Mon, 8/7/06, 8:30 AM - 5:00 PM CC-310
Generalized Linear and Latent Mixed Models - Continuing Education - Course
The ASA, Biometrics Section
Instructor(s): Sophia Rabe-Hesketh, University of California, Berkeley, Anders Skrondal, London School of Economics
Generalized linear mixed (or multilevel) models (GLMMs) are useful for longitudinal data, cluster-randomized trials, surveys with cluster-sampling, genetic studies, metaanalysis, etc. The random effects in GLMMs are latent variables representing between-cluster variability and inducing within-cluster dependence. Latent variables also are used often to represent true values of variables measured with error. Measurement models specifying the relationship between measured and latent variables can form part of regression models, giving structural equation models (SEMs). SEMs also can be used to model dependence between processes. Taking a unified view of these models is beneficial because developments for one model-type are applicable to other model-types and the same software can be used for seemingly different models. The course will be structured in three parts: GLMMs, measurement models, and SEMs. Ideas will be developed by starting from simple versions of the models and motivating extensions through examples. Methods of estimation and prediction will be surveyed. Real applications will be considered from different disciplines. RECOMMENDED TEXTBOOK: Skrondal, A. and Rabe-Hasketh, S. (2004): Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models. Chapman and Hall/CRC Press. ISBN: 1-58488-000-7.

Course attendees are expected to be familiar with the topic at the level of:
Generalized Linear Models by P. McCullagh and J.A. Nelder, Chapman & Hall/CRC Press.

 

JSM 2006 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised April, 2006