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Activity Number:
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277
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #304834 |
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Title:
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Semiparametric Cure Rate Models for Current Status Data
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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, MS 4A7, Fairfax, VA, 22030,
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Keywords:
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current status data ; semiparametric models ; cure rate models
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Abstract:
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In this research we study a class of semiparametric cure rate models for the analysis of current status data. This class includes the commonly used mixture cure rate model and proportional hazards cure model as special cases. We show that the nonparametric maximum likelihood estimators for the regression parameters of these models are consistent, asymptotically normal, and asymptotically efficient. We conduct extensive simulation studies to evaluate the performance of the proposed method. An illustration with a real study is provided.
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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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