Accelerated hazards mixture cure model |
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Authors: | Jiajia Zhang Yingwei Peng |
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Institution: | (1) Division of Biostatistics, School of Medicine, New York University, 650 First Ave, 526, New York, NY 10016, USA;(2) Department of Statistics, North Carolina State University, Raleigh, NC, USA |
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Abstract: | We propose a new cure model for survival data with a surviving or cure fraction. The new model is a mixture cure model where
the covariate effects on the proportion of cure and the distribution of the failure time of uncured patients are separately
modeled. Unlike the existing mixture cure models, the new model allows covariate effects on the failure time distribution
of uncured patients to be negligible at time zero and to increase as time goes by. Such a model is particularly useful in
some cancer treatments when the treat effect increases gradually from zero, and the existing models usually cannot handle
this situation properly. We develop a rank based semiparametric estimation method to obtain the maximum likelihood estimates
of the parameters in the model. We compare it with existing models and methods via a simulation study, and apply the model
to a breast cancer data set. The numerical studies show that the new model provides a useful addition to the cure model literature. |
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