SREL Reprint #2875

Bootstrap hypothesis testing and power analysis at low dose levels

Machelle D. Wilson

The University of Georgia, Savannah River Ecology Lab, P.O. Drawer E, Aiken, SC 29802 USA

Abstract: This study demonstrates the variability in dose estimates using the nonparametric bootstrap to estimate the variability in the mean dose when mean values from environmental data are used in the dose calculation. Bootstrap hypothesis testing and power analysis are demonstrated. For the data set shown here, the normal assumption works well if the environmental data can be considered fixed, known constants. However, when there exists a good deal of variability in the environmental data, as is most often the case, or where scarce data are available, making a normal assumption leads to gross underestimation of the variability in the mean dose.

Keywords: Bootstrap; Power analysis; Hypothesis testing; Incurred radioactive dose

SREL Reprint #2875

Wilson, M. D. 2005. Bootstrap hypothesis testing and power analysis at low dose levels. Science of the Total Environment 346:38-47.

This information was provided by the University of Georgia's Savannah River Ecology Laboratory (srel.uga.edu).