COMPARATIVE BIAS ASSOCIATED WITH VARIOUS ESTIMATES
OF DOSE TO MAXIMALLY EXPOSED INDIVIDUALS
M. D. Wilson and T. G. Hinton
Abstract-Protection of the environment from anthropogenic radiation is a resurging international interest. The paradigm currently in use argues that the population is adequately protected if dose rates to the maximally exposed individuals are below a certain limit. Based on data sampled from natural populations, resource managers need to be able to test the hypothesis that dose rates to the maximally exposed individu- als are acceptable. Recognizing the difficulty of sampling the maximally exposed individual within a contaminated environ- ment, risk assessors have used various alternative approaches that vary from changing the paradigm and applying recom- mended dose rate limits to representatively, rather than max- imally, exposed individuals, to using the 95th percentile of the sample mean as an estimator of the population maximum. To determine the effectiveness of numerous proposed alternatives, we used computer simulation techniques to generate a "popu- lation" of doses with known distributional qualities and then mathematically "sampled" the population to compare the ability of the various statistics at estimating the known popu- lation maximum. The simulation procedure was repeated 1000 times using Monte Carlo techniques, each time producing a measure of the distance between the estimate and the true value. We were thus able to quantify the bias associated with several approaches used to determine compliance with dose rate criteria established by the Department of Energy for protecting biota. The 95th quantile of the sample mean, and the sample maximum underestimated the population maxi- mum by as much as 72 and 44%, respectively. The maximum likelihood estimate (MLE) of the 99.99th percentile was found to be the best predictor of the population maximum, even for small sample sizes of 20 and for both normally and lognor- mally distributed populations. However, bias associated with the MLE increased significantly if the population's distribu- tion was incorrectly identified. We suggest shifting the regu- latory criterion appropriately to argue that if the top 1 % (as opposed to the maximum) of the population has a dose rate less than or equal to the regulatory limit then the population is adequately protected, and then using the MLE of the 99th percentile as the least biased sample statistic. Results of this study are also relevant when estimating dose to critical sub- groups of humans whose lifestyles are such that their doses are among the maximum for the population.
Key words: contamination, environmental; exposure, population;
maximum permissible concentrations; safety standards
SREL Reprint #2706
Wilson, M. D. and T. G. Hinton. 2003. Comparative bias associated with various estimates of dose to maximally exposed individuals. Health Physics 85:585-593.
