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A semi‐parametric accelerated failure time cure model
Author(s) -
Li ChinShang,
Taylor Jeremy M. G.
Publication year - 2002
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1260
Subject(s) - accelerated failure time model , logistic regression , covariate , computer science , parametric statistics , statistics , proportional hazards model , latency (audio) , incidence (geometry) , event data , event (particle physics) , econometrics , mathematics , telecommunications , physics , geometry , quantum mechanics
A cure model is a useful approach for analysing failure time data in which some subjects could eventually experience, and others never experience, the event of interest. A cure model has two components: incidence which indicates whether the event could eventually occur and latency which denotes when the event will occur given the subject is susceptible to the event. In this paper, we propose a semi‐parametric cure model in which covariates can affect both the incidence and the latency. A logistic regression model is proposed for the incidence, and the latency is determined by an accelerated failure time regression model with unspecified error distribution. An EM algorithm is developed to fit the model. The procedure is applied to a data set of tonsil cancer patients treated with radiation therapy. Copyright © 2002 John Wiley & Sons, Ltd.