Statistical limitations in relation to sample size.
The statistical difficulties of estimating cancer risks from low doses of a carcinogen are illustrated by examples from radiation carcinogenesis. Although more is known about dose-response relationships for ionizing radiation than for any other environmental carcinogen, estimates of cancer risk from low radiation doses have been extremely controversial; disagreements by factors of 100 or more are not uncommon. Direct estimation, based on data from populations exposed to low doses, is usually impracticable because of sample size requirements. Curve-fitting analyses, by which higher dose data determine lower dose risk estimates, require simple dose-response models if the estimates are to be statistically stable. The current level of knowledge about biological mechanisms of carcinogenesis dose not usually permit the confident assumption of a simple model, however; thus frequently the choice is between unstable risk estimates obtained using general models and statistically stable estimates whose stability depends on arbitrary model assumptions.
D000328:Adult; D001943:Breast Neoplasms / Q000209:etiology; D004307:Dose-Response Relationship, Radiation; D005260:Female; D006801:Humans; D007953:Leukemia, Radiation-Induced / Q000453:epidemiology; D009381:Neoplasms, Radiation-Induced / Q000453:epidemiology*; D012306:Risk; D012494:Sampling Studies / Q000379:methods; D013223:Statistics as Topic