An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies

We present a novel nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages. The asymptotic theory for the methodology is derived, showing that the MISEs (mean integrated squared error) of the estimates of both the dose-response curve F and its inverse F-1 achieve the optimal rate O(N-4/5). Also, we compute the asymptotic distribution of the estimate of the effective dosage [zeta]p=F-1(p) which is shown to have an optimally small asymptotic variance.