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Abstract Details
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Activity Number:
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553
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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ENAR
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| Abstract - #304940 |
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Title:
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Analysis of Failure Time Using Threshold Regression with Semiparametric Varying Coefficients
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Author(s):
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Jialiang Li*+ and Mei-Ling Ting Lee
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Companies:
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Duke-NUS Graduate Medical School and University of Maryland
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Address:
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Duke-NUS Graduate Medical School, Singapore, ,
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Keywords:
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Wiener process ;
Varying coefficients model ;
Inverse Gaussian distribution ;
Survival analysis ;
Semiparametric inference
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Abstract:
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Many new statistical models may enjoy better interpretability and numerical stability than traditional models in survival data analysis. Specifically, the threshold regression technique based on the inverse Gaussian distribution is a useful alternative to the Cox proportional hazards model to analyze lifetime data. In this paper we consider a semiparametric modelling approach for threshold regression and contribute implementational and theoretical details for model fitting and statistical inferences. Extensive simulations are carried out to examine the finite sample performance of the parametric and nonparametric estimates. A real example is analyzed to illustrate our methods, along with a careful diagnosis of model assumptions.
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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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