Abstract
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.
Original language | English (US) |
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Pages (from-to) | 389-395 |
Number of pages | 7 |
Journal | Statistics and Probability Letters |
Volume | 54 |
Issue number | 4 |
DOIs | |
State | Published - Oct 15 2001 |
Externally published | Yes |
Keywords
- Cure model
- Latency
- Logistic-Kaplan-Meier model
- Logistic-proportional hazards model
- Long-term incidence
ASJC Scopus subject areas
- Statistics, Probability and Uncertainty
- Statistics and Probability