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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...
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
1981
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1568793/ https://www.ncbi.nlm.nih.gov/pubmed/7333252 |
Sumario: | 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. |
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