Semiparametric accelerated failure time cure rate mixture models with competing risks
نویسندگان
چکیده
منابع مشابه
Semiparametric analysis of mixture regression models with competing risks data.
In the analysis of competing risks data, cumulative incidence function is a useful summary of the overall crude risk for a failure type of interest. Mixture regression modeling has served as a natural approach to performing covariate analysis based on this quantity. However, existing mixture regression methods with competing risks data either impose parametric assumptions on the conditional ris...
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We provide new conditions for identification of accelerated failure time competing risks models. These include Roy models and some auction models. In our set up, unknown regression functions and the joint survivor function of latent disturbance terms are all nonparametric. We show that this model is identified given covariates that are independent of latent errors, provided that a certain rank ...
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We extend the Dahlberg and Wang (Biometrics 2007, 63, 1237-1244) proportional hazards (PH) cure model for the analysis of time-to-event data that is subject to a cure rate with masked event to a setting where the PH assumption does not hold. Assuming an accelerated failure time (AFT) model with unspecified error distribution for the time to the event of interest, we propose rank-based estimatin...
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ژورنال
عنوان ژورنال: Statistics in Medicine
سال: 2017
ISSN: 0277-6715,1097-0258
DOI: 10.1002/sim.7508