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Identifiability of cure models

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

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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 54 (2001)
    Issue (Month): 4 (October)
    Pages: 389-395

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    Handle: RePEc:eee:stapro:v:54:y:2001:i:4:p:389-395

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    Related research

    Keywords: Cure model Latency Long-term incidence Logistic-Kaplan-Meier model Logistic-proportional hazards model;

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    Cited by:
    1. Yu, Binbing & Peng, Yingwei, 2008. "Mixture cure models for multivariate survival data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1524-1532, January.
    2. Borges, Patrick & Rodrigues, Josemar & Balakrishnan, Narayanaswamy, 2012. "Correlated destructive generalized power series cure rate models and associated inference with an application to a cutaneous melanoma data," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1703-1713.
    3. Shuangge Ma, 2011. "Additive risk model for current status data with a cured subgroup," Annals of the Institute of Statistical Mathematics, Springer, vol. 63(1), pages 117-134, February.
    4. He, Xuming & Xue, Hongqi & Shi, Ning-Zhong, 2010. "Sieve maximum likelihood estimation for doubly semiparametric zero-inflated Poisson models," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2026-2038, October.
    5. Peng, Yingwei & Zhang, Jiajia, 2008. "Identifiability of a mixture cure frailty model," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2604-2608, November.

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