Main Radiation Risk Estimation: Based on Measurement Error Models
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Radiation Risk Estimation: 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 covariatesMeasurement error modelsLinear models with classical errorPolynomial regression with known variance of classical errorNonlinear and generalized linear models

Part II Radiation risk estimation under uncertainty in exposure dosesOverview of risk models realized in program package EPICUREEstimation of radiation risk under classical or Berkson multiplicative error in exposure dosesRadiation risk estimation for persons exposed by radioiodine as a result of the Chornobyl accidentElements of estimating equations theoryConsistency of efficient methodsEfficient SIMEX method as a combination of the SIMEX method and the corrected score methodApplication of regression calibration in the model with additive error in exposure doses


Request Code : ZLIBIO2133230
Categories:
Year:
2017
Edition:
1
Publisher:
Walter De Gruyter Inc
Language:
English
Pages:
288
ISBN 10:
3110433672
ISBN:
3110441802,978-3-11-044180-2,978-3-11-043367-8,3110433672,978-3-11-043366-1,978-3-11-043347-0
Series:
De Gruyter series in mathematics and life sciences volume 5

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