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A statistical method for judging synergism: application to an endocrine disruptor animal experiment

机译:一种判断协同作用的统计方法:应用于内分泌干扰物动物实验

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This article proposes a statistical method for judging whether or not the combined action of chemicals is synergistic, being focused on the case in which two or more endocrine disruptors are made to act simultaneously. After defining synergism, the synergistic relation of two chemicals is formulated for a higher response than that expected under an exchangeable relation between them. Using this formulation as a basis, we then rationalize the triangular design for an animal experiment in which all dose settings are controlled within a triangle domain that prescribes the sum of doses of simultaneously applied chemicals less than a certain level. In addition, a statistical test is proposed for judging the synergism among chemicals used in animal experiments, i.e. the test evaluates the discrepancy between the observed mean response from simultaneous administration groups of chemicals and an estimated response under the null hypothesis of zero interaction based on data from single administration groups. Finally, test performance is examined using a simulation study and a case study―the rodent uterotrophic assay. The simulation study revealed that the test is not superior in power to the standard analysis of variance test based on a linear model with interaction term, yet robust in the sense that type I errors under variance heterogeneity were better controlled using Welch correction than the analysis of variance test. The application of the proposed statistical test to an animal experiment is considered acceptable based on results.
机译:本文提出了一种统计方法,用于判断化学物质的联合作用是否具有协同作用,重点是使两个或多个内分泌干扰物同时作用的情况。在定义了协同作用之后,两种化学物质的协同关系被制定为具有比在它们之间可交换关系下预期的响应更高的响应。然后,以这种配方为基础,我们对动物实验的三角形设计进行了合理化设计,在该设计中,所有剂量设置均控制在三角形域内,该域规定了同时施用的化学药品的剂量之和小于一定水平。另外,提出了一种统计测试来判断动物实验中使用的化学药品之间的协同作用,即该测试根据数据零相互作用的零假设在观察到的同时给予化学药品的平均响应与估计响应之间的差异。来自单个管理组。最后,通过模拟研究和案例研究(啮齿动物子宫营养测定)来检验测试性能。仿真研究表明,该测试的性能不优于基于带有交互项的线性模型的方差测试的标准分析,但在一定程度上具有稳健性,因为使用Welch校正比方差分析更好地控制了方差异质性下的I型错误。方差检验。根据结果​​,将建议的统计检验应用于动物实验被认为是可以接受的。

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