Sección: ArtículosTítulo: Benchmark dose analysis via nonparametric regression modeling / Walter W. Piegorsch...[et.al]Notas: Sumario: Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose-response modeling. It is a well-known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low-dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal-response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap-based confidence limits for the BMD. We explore the confidence limits¿ small-sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty.Registros relacionados: En: Risk analysis : an international journal. - McLean, Virginia : Society for Risk Analysis, 1987-2015 = ISSN 0272-4332. - 13/01/2014 Volumen 34 Número 1 - enero 2014 Otras clasificaciones: 7Derechos: In Copyright (InC)Referencias externas:
