title: Estimation of health risks associated with occupational radiation exposure: addressing measurement error and minimum detectable exposure level.
abstract: Occupational exposures are subject to several types of measurement errors. This paper considers two of the most common types of measurement error associated with occupational exposures: the error due to below minimum detection level and doses due to random measurement error. Doses are often recorded as zero when the exposure is below the minimum detection level. Values that are below the minimum detection level and are entered as zero lead to underestimation of the true exposure and can result in either an overestimate or underestimate of risk associated with the exposure. Random measurement error leads to an inefficient and attenuated estimate of risk associated with exposure. However, the levels of bias and inefficiency that can result from the simultaneous presence of both types of measurement error have not previously been studied. In addition, the impact of these measurement errors on the type I error and type II error for an exposure-response effect is unclear. Since the magnitude of the random error associated with cumulative exposure may vary with individuals and across time within an individual, traditional methods to correct for random measurement errors are not applicable here. Further, correcting errors for minimum detectable levels and random errors simultaneously is too complex for analytical solutions. Therefore, this paper uses simulation studies to quantitatively evaluate the magnitude of the bias, inefficiency, and type I and type II errors associated with them. The simulation results are applied to a sample of historical occupational radiation exposure data from the Oak Ridge National Laboratory. We conclude that after taking into consideration random measurement error and missed doses due to falling below the minimum detection level, radiation exposure is not significantly associated with all-cause mortality in that cohort.
authors.affiliation: Division of Biostatistics, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA. xxue@aecom.yu.edu
authors.forename: Xiaonan
authors.initials: X
authors.lastname: Xue
authors.forename: Mimi Y
authors.initials: MY
authors.lastname: Kim
authors.forename: Roy E
authors.initials: RE
authors.lastname: Shore
mesh_terms: D015982:Bias; D003198:Computer Simulation; D016273:Occupational Exposure / Q000009:adverse effects / Q000706:statistics & numerical data*; D016272:Occupational Health / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D011829:Radiation Dosage; D011834:Radiation Monitoring / Q000706:statistics & numerical data*; D012306:Risk; D012308:Risk Management