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Activity Number:
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377
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #303774 |
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Title:
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Modeling Smoking Cessation Data with Alternating States and a Cure Fraction Using Frailty Models
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Author(s):
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Yimei Li*+ and Paul E. Wileyto and Daniel F. Heitjan
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Companies:
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University of Pennsylvania and University of Pennsylvania and University of Pennsylvania
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Address:
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503 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104,
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Keywords:
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Addiction ; Copula ; Heterogeneity ; Multiple events ; Recurrent events
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Abstract:
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We propose a flexible parametric model to describe alternating-states recurrent-event data where there is a possibility of cure with each type of event. We begin by introducing a novel cure model where a common frailty influences both the cure probability and the hazard function given not cured. We then extend our model to data with recurring events of two, alternating types. We assume that each type of event has a gamma frailty, and we link the two frailties by means of a Clayton copula. We illustrate the model with an analysis of data from two smoking cessation trials comparing bupropion and placebo, in which each subject potentially experienced a series of lapse and recovery events. And our simulation study suggests that the estimates have little bias and that their 95% confidence intervals have nearly nominal coverage in samples of practical size.
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