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Activity Number:
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469
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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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Biometrics Section
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| Abstract - #308272 |
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Title:
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Empirical Likelihood-Based Inference for the Calibration Regression Model with Medical Cost
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Author(s):
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Yichuan Zhao*+
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Companies:
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Georgia State University
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Address:
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Department of Mathematics and Statistics, Atlanta, GA, 30303,
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Keywords:
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Abstract:
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Medical cost has received increasing interest recently in Biostatistics. Statistical analysis of life time medical cost has been challenging by the fact that the survival times are censored on some study subjects and their subsequent cost are unknown. Huang(2002) proposed the calibration regression model which is a semiparametric regression tool to study the medical cost associated with covariates. In this talk, an inference procedure is investigated using empirical likelihood (EL) method. An adjusted EL confidence region is constructed for the vector of regression parameters. We compare the proposed EL method with normal approximation method. Simulation results show that the proposed EL method outperforms the normal approximation method in terms of coverage probability. In particular, the adjusted empirical likelihood overcomes the under coverage problem.
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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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