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Comparing analytical results from different sources using nonidentical data sets

机译:使用不相同的数据集比较不同来源的分析结果

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摘要

Industrial corporations frequently require that different analytical facilities or instruments be compared with one another. Traditionally, the isoplot technique is used to accomplish this goal. This technique is only useful, however, when each subject has analyzed a large number of identical samples. Because this is not always the case, the present paper presents an alternate method of comparing analytical results. It is designed for cases where subjects have analyzed a relatively small number of trials from samples that are not identical. The proposed method uses normalized scores and ordinary least squares (OLS) linear regression. In the present, the proposed method use applied to a situation where the research team compared five different optical emission spectroscopy (OES) laboratories that had tested different sets of OES calibration standards. The normalized scores method provided a quantitative comparison of the laboratories in question. Based on this analysis, it is possible to conclude that one lab (B) clearly lagged behind the others, with respect to the precision of their analyses. It was also apparent that none of the labs were completely accurate. Each either overestimated or underestimated the calibrated element levels.
机译:工业公司经常要求将不同的分析设施或仪器进行相互比较。传统上,等位线技术用于实现此目标。但是,此技术仅在每个对象分析了大量相同的样本时才有用。由于并非总是如此,因此本文提出了一种比较分析结果的替代方法。它适用于受试者从不相同的样品中分析了相对较少的试验的情况。所提出的方法使用归一化分数和普通最小二乘(OLS)线性回归。目前,所提出的方法适用于以下情况:研究小组比较了五个不同的光学发射光谱(OES)实验室,这些实验室测试了不同的OES校准标准集。归一化分数法提供了有关实验室的定量比较。基于此分析,有可能得出结论,就分析的准确性而言,一个实验室(B)明显落后于其他实验室。显然,所有实验室都不是完全准确的。每个都高估或低估了校准元素的水平。

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