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A new inverse regression model applied to radiation biodosimetry
Author(s) -
Manuel Higueras,
Pedro Puig,
Elizabeth A. Ainsbury,
Kai Rothkamm
Publication year - 2015
Publication title -
proceedings of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2946
pISSN - 1364-5021
DOI - 10.1098/rspa.2014.0588
Subject(s) - biodosimetry , poisson distribution , poisson regression , negative binomial distribution , dosimetry , count data , hermite polynomials , mathematics , bayesian probability , ionizing radiation , computer science , statistics , physics , nuclear medicine , mathematical analysis , medicine , population , irradiation , environmental health , nuclear physics
Biological dosimetry based on chromosome aberration scoring in peripheral blood lymphocytes enables timely assessment of the ionizing radiation dose absorbed by an individual. Here, new Bayesian-type count data inverse regression methods are introduced for situations where responses are Poisson or two-parameter compound Poisson distributed. Our Poisson models are calculated in a closed form, by means of Hermite and negative binomial (NB) distributions. For compound Poisson responses, complete and simplified models are provided. The simplified models are also expressible in a closed form and involve the use of compound Hermite and compound NB distributions. Three examples of applications are given that demonstrate the usefulness of these methodologies in cytogenetic radiation biodosimetry and in radiotherapy. We provide R and SAS codes which reproduce these examples.

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