This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Activity Details

CE_17C Tue, 8/3/2010, 8:00 AM - 12:00 PM CC-8 (East)
Analysis of Longitudinal Data Using Antedependence Models — Continuing Education Course
Instructor(s): Dale Zimmerman, The University of Iowa
Antedependence models, also known as transition or Markov models, are useful generalizations of well-known stationary autoregressive models for longitudinal data. Like the latter models, antedependence models specify parsimonious parametric forms for the conditional mean and variance of each observation, given all the observations preceding it (as well as any observed covariates) on the same subject. Antedependence models differ, however, by allowing these forms to change over the course of the study, which makes them suitable for longitudinal data exhibiting nonstationary characteristics, e.g. increasing variances or same-lag correlations that change over time. The approach based on these models also provides important insights into the nature of the dependence structure of the data, which are not provided by a marginal or random-effects-based analysis. This course, which is based on the book of Zimmerman and Nunez-Anton (2009), introduces various antedependence models and describes methods of estimation, hypothesis testing, and model selection for them. Much of the course will consist of presentation of examples from the biological sciences, with analyses carried out using R and SAS. Participants should have a basic knowledge of longitudinal data analysis.

2010 JSM Online Program Home

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