JSM 2011 Online Program

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Abstract Details

Activity Number: 237
Type: Contributed
Date/Time: Monday, August 1, 2011 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #303394
Title: Cure Rate Models with Partially Observed Covariates
Author(s): Tzu-Chun Lin*+
Companies: University of California at Davis
Address: , , ,
Keywords: cure rate model ; partially observed covariates ; missing value ; nonparametric baseline hazard

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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