A primary objective in quantitative risk assessment is the characterization of risk which is defined to be the likelihood of an adverse effect caused by an environmental toxin or chemcial agent. In modern risk-benchmark analysis, attention centers on the “benchmark dose” at which a fixed benchmark level of risk is achieved, with a lower confidence limits on this dose being of primary interest. In practice, a range of benchmark risks may be under study, so that the individual lower confidence limits on benchmark dose must be corrected for simultaneity in order to maintain a specified overall level of confidence. For the case of quantal data, simultaneous methods have been constructed that appeal to the large sample normality of parameter estimates. The suitability of these methods for use with small sample sizes will be considered. A new bootstrap technique is proposed as an alternative to the large sample methodology. This technique is evaluated via a simulation study and examples from environmental toxicology.

中文翻译：

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使用量子响应数据进行同步基准分析的 Bootstrap 方法。

定量风险评估的主要目标是对风险进行表征，风险被定义为环境毒素或化学试剂引起不利影响的可能性。在现代风险基准分析中，注意力集中在达到固定基准风险水平的“基准剂量”上，主要关注的是该剂量的较低置信限。在实践中，可能正在研究一系列基准风险，因此必须针对同时性对基准剂量的个体置信下限进行修正，以保持特定的总体置信水平。对于量子数据的情况，已经构建了同步方法来吸引参数估计的大样本正态性。将考虑这些方法对小样本量的适用性。提出了一种新的引导程序技术作为大样本方法的替代方法。该技术通过模拟研究和环境毒理学示例进行评估。