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Activity Number:
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480
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #308778 |
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Title:
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Semiparametric Regression with Time-Dependent Coefficient for Failure Time Data Analysis
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Author(s):
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Zhangsheng Yu*+ and Xihong Lin
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Companies:
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The Ohio State University and Harvard School of Public Health
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Address:
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320 W 10th Avenue Rm B108, Columbus, OH, 48105,
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Keywords:
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Profile likelihood ; Clustered survival data ; Kernel smoothing ; Marginal model
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Abstract:
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We propose a working independent profile likelihood method for the semiparametric time-dependent coefficient model with correlation. Kernel likelihood is used to estimate time-dependent coefficient. Profile likelihood for the parametric coefficient is formed by plugging in the nonparametric estimator. For independent data, the estimator is asymptotically normal and achieves the asymptotic semiparametric efficiency bound. We evaluate the performance of proposed nonparametric kernel estimator and the profile estimator, and apply the method to the western Kenya parasitemia data.
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