title: Some statistical implications of dose uncertainty in radiation dose-response analyses.
abstract: Statistical dose-response analyses in radiation epidemiology can produce misleading results if they fail to account for radiation dose uncertainties. While dosimetries may differ substantially depending on the ways in which the subjects were exposed, the statistical problems typically involve a predominantly linear dose-response curve, multiple sources of uncertainty, and uncertainty magnitudes that are best characterized as proportional rather than additive. We discuss some basic statistical issues in this setting, including the bias and shape distortion induced by classical and Berkson uncertainties, the effect of uncertain dose-prediction model parameters on estimated dose-response curves, and some notes on statistical methods for dose-response estimation in the presence of radiation dose uncertainties.
authors.affiliation: Department of Statistics, Oregon State University, Corvallis, Oregon, USA. schafer@science.oregonstate.edu
authors.forename: Daniel W
authors.initials: DW
authors.lastname: Schafer
authors.forename: Ethel S
authors.initials: ES
authors.lastname: Gilbert
mesh_terms: D016477:Artifacts; D015982:Bias; D001822:Body Burden; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009381:Neoplasms, Radiation-Induced / Q000453:epidemiology*; D011829:Radiation Dosage; D011874:Radiometry / Q000379:methods*; D012062:Relative Biological Effectiveness; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors