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Activity Number:
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426
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #308200 |
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Title:
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Analysis of Smoking Cessation Patterns Using a Stochastic Mixed Effects Model with a Latent Cured State
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Author(s):
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Sheng Luo*+ and Ciprian M. Crainiceanu and Thomas A. Louis and Nilanjan Chatterjee
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Companies:
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Johns Hopkins University and Johns Hopkins University and Johns Hopkins University and National Cancer Institute
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Address:
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615 N Wolfe St, Dept. of Biostatistics, Baltimore, MD, 21205,
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Keywords:
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Cure Model ; Mixed-effect Model ; Recurrent Events ; Stochastic Transition Model ; Smoking Cessation
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Abstract:
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We develop a mixed model to capture the complex transition processes among addiction and non-addiction stages of tobacco dependence. An important innovation of our model is allowing an unobserved cure state, or permanent quitting, in contrast to transient quitting. This distinction is necessary when censoring prevents unambiguous determination of being "cured." We apply our methodology to a large (29,133 subjects) longitudinal study to model smoking cessation patterns using a discrete-time stochastic mixed-effect model with three states: smoking, transient cessation and permanent cessation. Random subject specific transition probabilities among these states are used to account for subject-to-subject heterogeneity. Another innovation is to design computationally practical methods using the marginal likelihood obtained by integrating over the Beta distribution of random effects.
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