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贝叶斯方法在生态毒理学中确定无效应浓度和危险浓度的应用。

A Bayesian approach for determining the no effect concentration and hazardous concentration in ecotoxicology.

机构信息

Australian Centre for Environmetrics, University of Melbourne, PO Box 4102, Parkville, Victoria, Australia.

出版信息

Ecotoxicol Environ Saf. 2010 Feb;73(2):123-31. doi: 10.1016/j.ecoenv.2009.09.012.

Abstract

This paper describes a Bayesian modeling approach to the estimation of the no effect concentration (NEC) and the hazardous concentration (HC(x)) as an alternative to conventional methods based on NOECs - the no observed effect concentration. The advantage of the proposed method is that it combines a plausible model for dose-response data with prior information or belief about the model's parameters to generate posterior distributions for the parameters - one of those being the NEC. The posterior distribution can be used to derive point and interval estimates for the NEC as well as providing uncertainty bounds when used in the development of a species sensitivity distribution (SSD). This latter feature is particularly attractive and overcomes a recognized deficiency of the NOEC-based approach. Examples using previously published data sets are provided which illustrate how the NEC/HC(x) estimation problem is re-cast and solved in this Bayesian framework.

摘要

本文描述了一种贝叶斯建模方法,用于估计无效应浓度 (NEC) 和危险浓度 (HC(x)),作为基于无观察效应浓度 (NOEC) 的传统方法的替代方法。该方法的优点在于,它将剂量反应数据的合理模型与模型参数的先验信息或置信度相结合,为参数生成后验分布——其中之一是 NEC。后验分布可用于为 NEC 生成点估计和区间估计,并在开发物种敏感性分布 (SSD) 时提供不确定性界限。当用于开发物种敏感性分布 (SSD) 时,这一特性特别有吸引力,并且克服了基于 NOEC 方法的一个公认缺陷。本文提供了使用先前发布的数据集的示例,说明了如何在这种贝叶斯框架中重新构建和解决 NEC/HC(x) 估计问题。

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