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Activity Number:
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347
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 14, 2002 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology*
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| Abstract - #301839 |
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Title:
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Longitudinal Categorical Data and Likelihood Inference
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Author(s):
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Patrick Heagerty*+
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Affiliation(s):
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University of Washington
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Address:
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Box 357232, Seattle, Washington, 98185, USA
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Keywords:
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Abstract:
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One common goal of a longitudinal study is to compare two or more groups with respect to their average response at various follow-up times. This talk will discuss flexible likelihood-based regression methods for the analysis of serial categorical data that can be used to estimate response profiles. The approach is called a "marginalized transition model" (Heagerty 2002, Biometrics) since the likelihood is constructed using two assumptions: a marginal mean regression model that characterizes systematic variation in the average response as a function of covariates (including group and time); and a Markov dependence model, or transition model, that describes serial correlation within an individual. One advantage to a likelihood approach is that a profile likelihood can guide selection of appropriate covariate transformations that may facilitate parsimonious models for group differences over time.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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