Power and Uncertainty Analysis of Epidemiological Studies of Radiation-Related Disease Risk in which Dose Estimates are Based on a Complex Dosimetry System: Some Observations
- 1 October 2003
- journal article
- research article
- Published by Radiation Research Society in Radiation Research
- Vol. 160 (4) , 408-417
- https://doi.org/10.1667/3046
Abstract
Stram, D. O. and Kopecky, K. J. Power and Uncertainty Analysis of Epidemiological Studies of Radiation-Related Disease Risk in which Dose Estimates are Based on a Complex Dosimetry System: Some Observations. Radiat. Res. 160, 408–417 (2003).This paper discusses practical effects of dosimetry error relevant to the design and analysis of an epidemiological study of disease risk and exposure. It focuses on shared error in radiation dose estimates for such studies as the Hanford Thyroid Disease Study or the Utah Thyroid Cohort Study, which use complex dosimetry systems that produce multiple replications of possible dose for the cohort. We argue that a simple estimation of shared multiplicative error components through direct examination of the replications of dose for each person provides information useful for estimating the power of a study to detect a radiation effect and illustrate this with an example based on the doses used for the Hanford Thyroid Disease Study. Uncertainty analysis (construction of confidence intervals) can be approached in the same way in simple cases. We also offer some suggestions for Monte Carlo-based confidence intervals.Keywords
This publication has 8 references indexed in Scilit:
- Risk estimates for radiation-induced cancer – the epidemiological evidenceRadiation and Environmental Biophysics, 2000
- Hanford Environmental Dose Reconstruction Project-An OverviewHealth Physics, 1996
- The Utah Thyroid Cohort StudyHealth Physics, 1995
- Exposure Measurement Error: Influence on Exposure-Disease Relationships and Methods of CorrectionAnnual Review of Public Health, 1993
- Regression With Missing X's: A ReviewJournal of the American Statistical Association, 1992
- The Errors-in-Variables Problem: Considerations Provided by Radiation Dose-Response Analyses of the A-Bomb Survivor DataJournal of the American Statistical Association, 1992
- Performing likelihood ratio tests with multiply-imputed data setsBiometrika, 1992
- Designing a logistic regression study using surrogate measures for exposure and outcomeBiometrika, 1990