Beyond the Domain of Direct Observation: How to Specify a Probability Distribution that Represents the ‘State of Knowledge’ About Uncertain Inputs

Publication Date Feb 28, 1999 by Hoffman O., Kaplan S.

Uncertainty is inherent in all exposure and risk assessments in which mathematical models are used to extrapolate information beyond the domain of direct observation. Uncertainty exists because models are imperfect mimics of reality.

In addition, the data available for inputs are seldom directly relevant to the defined assessment endpoint. For example, data on dietary habits are often composed of daily or weekly recall surveys which impart little information about the daily consumption rate averaged over a year to a lifetime which are the typical time periods required to estimate the excess lifetime risk to a potentially exposed individual.

Risk Analysis, Vol. 19, Issue No. 1, pp. 131-134.

Available from Wiley Online Library