Identifiability of cure models

Chin-Shang Li, Jeremy M G Taylor, Judy P. Sy

Research output: Contribution to journalArticle

97 Scopus citations

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 languageEnglish (US)
Pages (from-to)389-395
Number of pages7
JournalStatistics and Probability Letters
Volume54
Issue number4
DOIs
StatePublished - Oct 15 2001
Externally publishedYes

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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