Dose-response assessment by a fuzzy linear-regression method

Abstract

Regression analysis has been used to characterize the relationship between an exposure dose and the incidence of an adverse health effect such as cancer. However, the regression rarely describes the true relationship due to uncertainties in dose-response data and relationships. Therefore, a method is developed to perform dose-response assessments by a fuzzy linear regression which explicitly exhibit these uncertainties. This method is applied to define the relationship between a particular nitrate dose to humans and its corresponding cancer risk.

Analysis and propagation of uncertainties due to the stage–discharge relationship: a fuzzy set approach

“…This leads to an optimization problem, in which the objective function may be evaluated in terms of minimal uncertainty using several criteria, such as the maximum vagueness, the average vagueness and the prediction vagueness . Some of the examples of fuzzy regression analysis include the dose-response relationship (Bárdossy et al, 1993;Lee et al, 2001) and linear fuzzy conceptual rainfall-runoff processes (Özelkan & Duckstein, 2000).…”