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Abstract Details
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Activity Number:
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237
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #303394 |
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Title:
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Cure Rate Models with Partially Observed Covariates
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Author(s):
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Tzu-Chun Lin*+
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Companies:
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University of California at Davis
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Address:
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, , ,
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Keywords:
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cure rate model ;
partially observed covariates ;
missing value ;
nonparametric baseline hazard
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Abstract:
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Cure rate models are proposed to model time-to-event data with a significant fraction of subjects who are considered as long-term survivors. One design of these models is a mixture of a cure probability and a survivor function for the non-cured group with a non-cured probability. Meanwhile, partially observed covariates data are often encountered due to many reasons, and analysis only based on complete data will often result in bias estimates. This study aims to compare a logistic/generalized F mixture cure rate model with a commonly chosen model, a logistic/Weibull mixture cure rate model with covariates having missing values.
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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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