**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.
To request a reprint |