Recommendations on statistical approaches to account for dose uncertainties in radiation epidemiologic risk models

Author:

Bellamy Michael B.1ORCID,Bernstein Jonine L.2ORCID,Cullings Harry M.3ORCID,French Benjamin4ORCID,Grogan Helen A.5ORCID,Held Kathryn D.5ORCID,Little Mark P.67ORCID,Tekwe Carmen D.8ORCID

Affiliation:

1. Department of Medical Physics, Memorial Sloan Kettering Cancer Center New York, New York, NY, USA

2. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center New York, New York, NY, USA

3. Department of Statistics, Radiation Research Effects Foundation, Hiroshima, Japan

4. Vanderbilt University Medical Center, Nashville, TN, USA

5. NCRP, Bethesda, MD, USA

6. Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA

7. Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK

8. Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA

Publisher

Informa UK Limited

Reference74 articles.

1. Akaike H. 1973. Information theory and an extension of the maximum likelihood principle. In Petrov BN, Czáki F, editors. 2nd International Symposium on Information Theory. Budapest: Akadémiai Kiadó. p. 267–281.

2. Assessment of uncertainty associated with measuring exposure to radon and decay products in the French uranium miners cohort

3. Simulation–extrapolation method to address errors in atomic bomb survivor dosimetry on solid cancer and leukaemia mortality risk estimates, 1950–2003

4. Armstrong B, Brenner DJ, Baverstock K, Cardis E, Green A, Guilmette RA, Hall J, Hill MA, Hoel D, Krewski D, et al. 2012. Radiation. Volume 100D. A review of human carcinogens. Lyon, France: International Agency for Research on Cancer.

5. Reconstructed lung doses for the million person study cohort of 26,650 Tennessee Eastman corporation workers employed between 1942 and 1947

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