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Abstract Details
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Activity Number:
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340
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #305322 |
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Title:
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Semiparametric Analysis of Short-Term and Long-Term Odds Ratios with Survival Data
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Author(s):
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Mengdie Yuan*+ and Guoqing Diao
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Companies:
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George Mason University and George Mason University
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Address:
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Dept of Statistics,Engineering Building,MS 4A7, Fairfax, VA, 22030, United States
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Keywords:
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Non-parametric likelihood ;
Odds ratio ;
Proportional odds ;
Semiparametric efficiency
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Abstract:
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The proportional odds model is a popular model in survival analysis. The assumption of constant odds ratios over time in the proportional odds model, however, is often violated in many applications. We propose a novel semiparametric general odds ratio model for the analysis of right-censored survival data. The proposed model incorporates the short-term and long-term covariate effects on the failure time data and includes the proportional odds model as a special case. We derive efficient likelihood-based estimation and inference procedures and establish the large sample properties of the proposed nonparametric maximum likelihood estimators. Extensive simulation studies demonstrate the proposed methods perform well in practical settings. An application to a genetic study is provided.
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Authors who are presenting talks have a * after their name.
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