Assessing risk with doubly censored data: an application to the analysis of radiation-induced thyropathy

Ilya L. Kruglikov, Nikolaj I. Pilipenko, Alexander D. Tsodikov and Andrej Yu. Yakovlev

Statistics & Probability Letters, 1997, vol. 32, issue 3, 223-230

Abstract: This paper deals with the statistical inference from doubly censored data on the incidence of thyropathy in a group of liquidators of the Chernobyl accident with special emphasis on the long-term risk assessment. In this study, all sample observations are either left or right censored. The prime objective is to estimate the disease onset distribution and the expected proportion of responders (long-term risk) from real data of this type. We give a solution to this problem using a parametric family of improper distributions derived from a recently proposed model of radiation carcinogenesis (Klebanov et al., 1993).

Keywords: Left; and; right; censoring; Data; grouping; Onset; time; distribution; Nonparametric; estimation; Risk; assessment; Parametric; model; ML; estimates; Radiation-induced; thyropathy; Chernobyl; accident (search for similar items in EconPapers)
Date: 1997
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