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Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses

Author

Listed:
  • Kukush Alexander

    (Ukraine Radiation Protection Institute)

  • Shklyar Sergiy

    (Ukraine Radiation Protection Institute)

  • Masiuk Sergii

    (Ukraine Radiation Protection Institute)

  • Likhtarov Illya

    (Ukraine Radiation Protection Institute)

  • Kovgan Lina

    (Ukraine Radiation Protection Institute)

  • Carroll Raymond J

    (Texas A&M University)

  • Bouville Andre

    (National Cancer Institute, NIH, DHHS)

Abstract

With a binary response Y, the dose-response model under consideration is logistic in flavor with pr(Y=1 | D) = R (1+R)-1, R = λ0 + EAR D, where λ0 is the baseline incidence rate and EAR is the excess absolute risk per gray. The calculated thyroid dose of a person i is expressed as Dimes = fiQimes/Mimes. Here, Qimes is the measured content of radioiodine in the thyroid gland of person i at time tmes, Mimes is the estimate of the thyroid mass, and fi is the normalizing multiplier. The Qi and Mi are measured with multiplicative errors ViQ and ViM, so that Qimes = QitrViQ (this is classical measurement error model) and Mitr = MimesViM (this is Berkson measurement error model). Here, Qitr is the true content of radioactivity in the thyroid gland, and Mitr is the true value of the thyroid mass. The error in fi is much smaller than the errors in (Qimes, Mimes) and ignored in the analysis.

Suggested Citation

  • Kukush Alexander & Shklyar Sergiy & Masiuk Sergii & Likhtarov Illya & Kovgan Lina & Carroll Raymond J & Bouville Andre, 2011. "Methods for Estimation of Radiation Risk in Epidemiological Studies Accounting for Classical and Berkson Errors in Doses," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-30, February.
    • Handle: RePEc:bpj:ijbist:v:7:y:2011:i:1:n:15
    DOI: 10.2202/1557-4679.1281
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    References listed on IDEAS

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    1. Schneeweiss, Hans & Cheng, Chi-Lun, 2006. "Bias of the structural quasi-score estimator of a measurement error model under misspecification of the regressor distribution," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 455-473, February.
    2. Shklyar, S. & Schneeweiss, H., 2005. "A comparison of asymptotic covariance matrices of three consistent estimators in the Poisson regression model with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 250-270, June.
    3. Yehua Li & Annamaria Guolo & F. Owen Hoffman & Raymond J. Carroll, 2007. "Shared Uncertainty in Measurement Error Problems, with Application to Nevada Test Site Fallout Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1226-1236, December.
    4. Bani Mallick & F. Owen Hoffman & Raymond J. Carroll, 2002. "Semiparametric Regression Modeling with Mixtures of Berkson and Classical Error, with Application to Fallout from the Nevada Test Site," Biometrics, The International Biometric Society, vol. 58(1), pages 13-20, March.
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    Cited by:

    1. Mark P Little & Alexander G Kukush & Sergii V Masiuk & Sergiy Shklyar & Raymond J Carroll & Jay H Lubin & Deukwoo Kwon & Alina V Brenner & Mykola D Tronko & Kiyohiko Mabuchi & Tetiana I Bogdanova & Ma, 2014. "Impact of Uncertainties in Exposure Assessment on Estimates of Thyroid Cancer Risk among Ukrainian Children and Adolescents Exposed from the Chernobyl Accident," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-9, January.

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