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Activity Number:
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361
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Type:
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Invited
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Date/Time:
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Wednesday, August 1, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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WNAR
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| Abstract - #308008 |
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Title:
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Bayesian Modeling of Longitudinal Processes with Dropout and Noncompliance
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Author(s):
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Michael Daniels*+ and Xuefeng Liu
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Companies:
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University of Florida and Wayne State University
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Address:
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Department of Epidemiology and Biostatistics, Gainesville, FL, 32611,
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Keywords:
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Abstract:
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Joint models for the association of a longitudinal binary and continuous process are proposed for situations where their association is of direct interest. The models are parameterized such that the dependence between the two processes is characterized by unconstrained regression coefficients. Bayesian variable selection techniques are used to parsimoniously model these coefficients. An MCMC sampling algorithm is developed for sampling from the posterior distribution. The models are motivated by, and are used for, the analysis of a smoking cessation clinical trial in which an important question of interest was the effect of the (exercise) treatment on the relationship between smoking cessation and weight gain. In this trial, there was both dropout and noncompliance. We propose ways to adjust for both of these factors in our analysis.
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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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