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Activity Number:
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193
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Type:
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Topic Contributed
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Date/Time:
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Monday, July 30, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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WNAR
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| Abstract - #308331 |
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Title:
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Nonparametric Hazard Estimation for Gap Time in Recurrent Event Data
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Author(s):
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Pang Du*+
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Companies:
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Virginia Polytechnic Institute and State University
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Address:
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410 Hutcheson Hall, Blacksburg, VA, 24061-0439,
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Keywords:
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Recurrent event ; Gap time ; Hazard ; Penalized likelihood ; Asymptotic convergence rate ; Model Selection
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Abstract:
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Recurrent event data arise in many biomedical and engineering studies when failure events can occur repeatedly over time for each study subject. In this article, we are interested in nonparametric estimation of the hazard function for gap times. A penalized likelihood model is proposed to estimate the hazard as a function of both gap time and covariate. Method for smoothing parameter selection is developed and Bayesian confidence intervals for the hazard function are derived. Asymptotic convergence rates of the estimates are also established by assuming no gap times of a subject are the same. Empirical studies are performed to evaluate various aspects of the method. The exploratory role of the proposed technique is illustrated through an application to the well-known bladder tumor cancer data.
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