An integrated, quantitative approach to incorporating both uncertainty and interindividual variability into risk prediction models is described. Individual risk R is treated as a variable distributed in both an uncertainty dimension and a variability dimension, whereas population risk I (the number of additional cases caused by R) is purely uncertain. I is shown to follow a compound Poisson‐binomial distribution, which in low‐level risk contexts can often be approximated well by a corresponding compound Poisson distribution. The proposed analytic framework is illustrated with an application’to cancer risk assessment for a California population exposed to 1,2‐dibromo‐3‐chloropropane from ground water.
Risk Analysis – Wiley
Published: Dec 1, 1987
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