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Activity Number:
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485
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Type:
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Contributed
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Date/Time:
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Thursday, August 7, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #301868 |
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Title:
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Semiparametric Cure Rate Models with Random Effects
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Author(s):
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Guoqing Diao*+
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Companies:
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George Mason University
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Address:
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Department of Statistics, MSN 4A7, Fairfax, VA, 22030,
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Keywords:
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Box-Cox transformation ; cure fraction ; mixture cure model ; proportional hazards cure model
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Abstract:
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We propose a novel class of cure rate models for multivariate failure time data with a survival fraction. The class is formulated through a transformation on the unknown population survival function. It incorporates random effects to account for the underlying correlation, and includes the mixture cure model structure and the proportional hazards cure model structure as two special cases. We show that the nonparametric maximum likelihood estimators (NPMLE) for the parameters of these models are consistent and asymptotically normal. The limiting variances achieve the semiparametric efficiency bounds and can be consistently estimated. Simulation studies demonstrate that the proposed methods perform well in practical situations. This class of models is illustrated with a real example.
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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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