Nonparametric estimation of benchmark doses in environmental risk assessment

An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), which induce a pre-specified benchmark response in a doseresponse experiment. In such settings, representations of the risk are traditionally based on a parametric doseresponse model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating BMDs, based on an isotonic doseresponse estimator for quantal-response data. We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. Copyright (c) 2012 John Wiley & Sons, Ltd.