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 |
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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
Cite this
Identifiability of cure models. / Li, Chin-Shang; Taylor, Jeremy M G; Sy, Judy P.
In: Statistics and Probability Letters, Vol. 54, No. 4, 15.10.2001, p. 389-395.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Identifiability of cure models
AU - Li, Chin-Shang
AU - Taylor, Jeremy M G
AU - Sy, Judy P.
PY - 2001/10/15
Y1 - 2001/10/15
N2 - 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.
AB - 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.
KW - Cure model
KW - Latency
KW - Logistic-Kaplan-Meier model
KW - Logistic-proportional hazards model
KW - Long-term incidence
UR - http://www.scopus.com/inward/record.url?scp=0005091283&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0005091283&partnerID=8YFLogxK
U2 - 10.1016/S0167-7152(01)00105-5
DO - 10.1016/S0167-7152(01)00105-5
M3 - Article
VL - 54
SP - 389
EP - 395
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
SN - 0167-7152
IS - 4
ER -