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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 - #301640 |
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Title:
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Partially Functional Quantile Regression Model for Survival Data
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Author(s):
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Jing Qian*+ and Limin Peng+
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Companies:
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Emory University and Emory University
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Address:
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1518 Clifton RD NE 3rd FL, Atlanta, GA, 30322, 1518 Clifton RD NE 3rd FL, Atlanta, GA, 30322,
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Keywords:
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Censoring ; Empirical Process ; Martingale ; Regression Quantiles ; Resampling
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Abstract:
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Quantile regression has received increased attention in survival analysis because of its good interpretability and great flexibility. In recent work by Peng and Huang (2008), a new censored quantile regression approach has been developed by utilizing the inherent martingale structure of survival data, without requiring stringent censoring assumption and involving complicated algorithms. In this paper we further extend Peng and Huang (2008)'s technique to partially functional quantile regression model, which in reality is expected to achieve a better balance between efficiency and robustness than the standard fully model. We establish the asymptotic properties of the resultant estimators and develop a simple resampling inference procedure. The finite-sample performance of the proposed method is evaluated via simulation studies and illustrated with an application to a dialysis study.
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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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