Sergii Masiuk & Alexander Kukush 
Radiation Risk Estimation [EPUB ebook] 
Based on Measurement Error Models

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This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.

Contents:


Part I – Estimation in regression models with errors in covariates
Measurement error models
Linear models with classical error
Polynomial regression with known variance of classical error
Nonlinear and generalized linear models


Part II Radiation risk estimation under uncertainty in exposure doses
Overview of risk models realized in program package EPICURE
Estimation of radiation risk under classical or Berkson multiplicative error in exposure doses
Radiation risk estimation for persons exposed by radioiodine as a result of the Chornobyl accident
Elements of estimating equations theory
Consistency of efficient methods
Efficient SIMEX method as a combination of the SIMEX method and the corrected score method
Application of regression calibration in the model with additive error in exposure doses

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A propos de l’auteur

S. Masiuk, A. Kukush, S. Shklyar, M. Chepurny, I. Likhtarov, Radiation Protection Institute, Ukraine.

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Langue Anglais ● Format EPUB ● Pages 270 ● ISBN 9783110433470 ● Taille du fichier 11.5 MB ● Maison d’édition De Gruyter ● Lieu Berlin/Boston ● Publié 2017 ● Édition 1 ● Téléchargeable 24 mois ● Devise EUR ● ID 6586082 ● Protection contre la copie Adobe DRM
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