Advances and Applications in Statistics
Volume 14, Issue 1, Pages 1 - 16
(January 2010)
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A MULTIPLE TIME SCALE SURVIVAL MODEL
Francisco Louzada-Neto and Juliana Cobre
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Abstract: Several areas such as biomedical, criminology, financial, among others, may present recurrent events for the same individual. In this paper, we propose a multiple time scale survival model to analyze recurrent event data. The general framework accommodates a broad class of survival models including the Poisson, renewal and count models as special cases. We envisage applications in which only one individual, or moderate or large number of individuals, has been observed and the number of events per individual may be small or moderate. All estimates are obtained through a sampling based approach, which allows information to be input beforehand with lower computational effort. Simulations are realized based on a clinical scenario in order to verify some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. The methodology is illustrated on a real data set. |
Keywords and phrases: multiple time scales, recurrent event data, coverage probability, Bayesian approach. |
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