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Detection limits and goodness-of-fit measures for the two-component model of chemical analytical error

机译:化学分析误差两成分模型的检出限和拟合优度

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摘要

The utility of analytical chemistry measurements in most applications is dependent on an assessment of measurement error. This paper demonstrates the use of a two-component error model in setting limits of detection and related concepts and introduces two goodness-of-fit statistics for assessing the appropriateness of the model for the data at hand. The model is applicable to analytical methods in which high concentrations are measured with approximately constant relative standard deviation. At low levels, the relative standard deviation cannot stay constant, since this implies vanishingly small absolute standard deviation. The two-component model has approximately constant standard deviation near zero concentration, and approximately constant relative standard deviation at high concentrations, a pattern that is frequently observed in practice. Here we discuss several important applications of the model to environmental monitoring and also introduce two goodness-of-fit statistics, to ascertain whether the data exhibit the error structure assumed by the model, as well as to took for problems with experimental design. (C) 2004 Elsevier B.V. All rights reserved. [References: 17]
机译:分析化学测量在大多数应用中的效用取决于对测量误差的评估。本文演示了在设置检测极限和相关概念时使用两成分误差模型,并介绍了两个拟合优度统计信息,以评估该模型对于手头数据的适用性。该模型适用于以近似恒定的相对标准偏差测量高浓度的分析方法。在低水平下,相对标准偏差不能保持恒定,因为这意味着绝对标准偏差逐渐消失。两组分模型在零浓度附近具有近似恒定的标准偏差,在高浓度下具有近似恒定的相对标准偏差,这是在实践中经常观察到的模式。在这里,我们讨论了该模型在环境监测中的几个重要应用,还介绍了两个拟合优度统计数据,以确定数据是否表现出模型所假设的错误结构,并考虑了实验设计中的问题。 (C)2004 Elsevier B.V.保留所有权利。 [参考:17]

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