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Nonparametric estimation of the hazard function by using a model selection method: estimation of cancer deaths in Hiroshima atomic bomb survivors

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Controversy has intensified regarding the death-rate from cancer that is induced by a dose of radiation. In the models that are usually considered the hazard function is an increasing function of the dose of radiation. Such models can mask local variations. We consider the models of excess relative risk and of absolute risk and propose a nonparametric estimation of the effect of the dose by using a model selection procedure. This estimation deals with stratified data. We approximate the function of the dose by a collection of splines and select the best one according to the Akaike information criterion. In the same way between the models of excess relative risk or excess absolute risk, we choose the model that best fits the data. We propose a bootstrap method for calculating a pointwise confidence interval of the dose function. We apply our method for estimating the solid cancer and leukaemia death hazard functions to Hiroshima.

Keywords: Bootstrap; Hazard function; Model of excess absolute risk; Model of excess relative risk; Model selection; Nonparametric estimation; Spline functions

Document Type: Research Article


Affiliations: Institut National Agronomique Paris-Grignon, Mathématique et Informatique Appliquées, Paris, and Institut National de la Recherche Agronomique, Unité de Recherche en Genomique Végétale, Evry, France

Publication date: April 1, 2005

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