Bootstrap hypothesis testing and power analysis at low dose levels.
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.
Wilson
Machelle D
MD
The University of Georgia, Savannah River Ecology Lab, Aiken, SC 29801, USA. wilson@srel.edu
D000818:Animals; D004305:Dose-Response Relationship, Drug; D004785:Environmental Pollutants / Q000633:toxicity*; D015233:Models, Statistical; D018675:Toxicity Tests
D004785:Environmental Pollutants