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) |
|---|---|
| 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
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Cite this
Li, C-S., Taylor, J. M. G., & Sy, J. P. (2001). Identifiability of cure models. Statistics and Probability Letters, 54(4), 389-395. https://doi.org/10.1016/S0167-7152(01)00105-5