In modern environmental risk analysis, inferences are often desired on those low dose levels at which a fixed benchmark risk is achieved. In this paper, we study the use of confidence limits on parameters from a simple one-stage model of risk historically popular in benchmark analysis with quantal data. Based on these confidence bounds, we present methods for deriving upper confidence limits on extra risk and lower bounds on the benchmark dose. The methods are seen to extend automatically to the case where simultaneous inferences are desired at multiple doses. Monte Carlo evaluations explore characteristics of the parameter estimates and the confidence limits under this setting.

中文翻译：

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基准风险评估中对单阶段模型参数的置信限制。

在现代环境风险分析中，通常需要对达到固定基准风险的那些低剂量水平进行推断。在本文中，我们研究了对参数的置信限制的使用，该模型来自一个简单的单阶段风险模型，该模型在使用量子数据的基准分析中历来流行。基于这些置信界限，我们提出了用于推导额外风险的置信上限和基准剂量的下限的方法。可以看到这些方法自动扩展到需要在多个剂量下同时进行推断的情况。Monte Carlo 评估探索了在此设置下参数估计的特征和置信限。