Probabilistic risk assessment's use of trees and distributions to reflect uncertainty and variability and to overcome the limitations of default assumptions

摘要: Abstract Probabilistic risk assessment is an emerging approach to exposure and quantitative cancer non-cancer characterizations. The easily extended other types of risks outcomes. A tree, like a decision tree or probability encourages the evaluation not only default assumptions but also alternatives those defaults, reflects uncertainty in current state knowledge. Trees are used both characterization dose received by individuals potential situation dose-response relationship for specified response concern. Probability distributions reflect variability exposure, dose, relationships among over time within individuals. Distributions incorporating variabilities, uncertainties, subjective probabilities, expert judgments characterize probabilities observing individual population with from certain adverse health effect designated (i.e., risk). Some suggestions given on how manager can incorporate distributional into making. discussion included concerning sensitivity analyses path analyses. major finding methodology explicitly variability, uncertainty, defaults dose-response,