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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 dose–response experiment. In such settings, representations of the risk are traditionally based on a parametric dose–response 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 dose–response 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 © 2012 John Wiley & Sons, Ltd.
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 dose–response experiment. In such settings, representations of the risk are traditionally based on a parametric dose–response 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 dose–response 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 © 2012 John Wiley & Sons, Ltd.
Nonparametric estimation of benchmark doses in environmental risk assessment
Piegorsch, Walter W. (Autor:in) / Xiong, Hui (Autor:in) / Bhattacharya, Rabi N. (Autor:in) / Lin, Lizhen (Autor:in)
Environmetrics ; 23 ; 717-728
01.12.2012
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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