Identifiability of cure models
Cure models can be used for censored survival data in which a fraction of the observations do not exhibit the event of interest despite long-term follow-up. In this paper we investigate the identifiability of two forms of the cure model, a standard cure model based on a mixture distribution and a non-mixture proportional hazards (PH) model with long-term survivors. In the standard cure model, except for the case where the conditional survival function is independent of covariates and the mixture probability is an arbitrary function of a covariate we show that the parameters of the standard cure model are identified. In the non-mixture PH model, we show the model is identifiable if the distribution function is specified.
Year of publication: |
2001
|
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Authors: | Li, Chin-Shang ; Taylor, Jeremy M. G. ; Sy, Judy P. |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 54.2001, 4, p. 389-395
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Publisher: |
Elsevier |
Keywords: | Cure model Latency Long-term incidence Logistic-Kaplan-Meier model Logistic-proportional hazards model |
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