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Semiparametric analysis of clustered survival data under nonparametric frailty

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  • Malay Naskar

Abstract

In this article a novel approach to analyze clustered survival data that are subject to extravariation encountered through clustering of survival times is proposed. This is accomplished by extending the Cox proportional hazard model to a frailty model where the cluster‐specific shared frailty is modeled nonparametrically. We assume a nonparametric Dirichlet process for the distribution of frailty. In such a semiparametric setup, we propose a hybrid method to draw model‐based inferences. In the framework of the proposed hybrid method, the estimation of parameters is performed by implementing Monte Carlo expected conditional maximization algorithm. A simulation study is conducted to study the efficiency of our methodology. The proposed methodology is, thereafter, illustrated by a real‐life data on recurrence time to infections in kidney patient.

Suggested Citation

  • Malay Naskar, 2008. "Semiparametric analysis of clustered survival data under nonparametric frailty," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(2), pages 155-172, May.
  • Handle: RePEc:bla:stanee:v:62:y:2008:i:2:p:155-172
    DOI: 10.1111/j.1467-9574.2007.00372.x
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