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Integrating Uncertainty and Interindividual Variability in Environmental Risk Assessment
Author(s) -
Bogen Kenneth T.,
Spear Robert C.
Publication year - 1987
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1987.tb00480.x
Subject(s) - poisson distribution , dimension (graph theory) , risk assessment , statistics , binomial distribution , population , mathematics , poisson regression , variable (mathematics) , negative binomial distribution , distribution (mathematics) , econometrics , computer science , environmental health , medicine , computer security , pure mathematics , mathematical analysis
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.