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分析化学中的偏差:综述了一些将未修正的偏差纳入分析测量扩展不确定度的选定程序,以及一种评估参考和测试程序一致性的图形方法。

Bias in analytical chemistry: A review of selected procedures for incorporating uncorrected bias into the expanded uncertainty of analytical measurements and a graphical method for evaluating the concordance of reference and test procedures.

机构信息

96 Shirley Road, Roseville, New South Wales 2069, Australia.

Discipline of Laboratory Medicine, School of Health and Biomedical Sciences, RMIT University, Bundoora, Victoria 3083, Australia.

出版信息

Clin Chim Acta. 2019 Aug;495:129-138. doi: 10.1016/j.cca.2019.03.1633. Epub 2019 Mar 29.

DOI:10.1016/j.cca.2019.03.1633
PMID:30935874
Abstract

The Evaluation of measurement data - Guide to the Expression of Uncertainty in Measurement (GUM) provides the framework for evaluating measurement uncertainty. The preferred GUM approach for addressing bias assumes that all systematic errors are identified and corrected at an early stage in the measurement process. We review some procedures for treating uncorrected bias and its inclusion into an overall uncertainty statement. When bias and its uncertainty are recognised as metrological states independent of scatter in the test results, the uncertainty of the reference and uncertainty of the bias can be equated. The net standard uncertainty of a test result is the root-sum-square of the standard uncertainty of the bias and the standard uncertainty of measurements on the test. Since an incomplete and therefore potentially erroneous formula is often used for estimating bias standard uncertainty, we propose an alternative calculation. We next propose a graphical method using a simple algorithm that quantifies the discrepancy between the results of a test measurement and the corresponding reference value, in terms of the percentage overlap of two probability density functions. We propose that bias should be corrected wherever possible and we illustrate this approach using the graphical method. Even though this review is focused principally on analytical chemistry and medical laboratory applications, much of the discussion is applicable to all areas of metrology.

摘要

测量数据的评估——测量不确定度表示的指南(GUM)提供了评估测量不确定度的框架。在测量过程的早期阶段,处理未校正偏差及其包含在总体不确定度声明中的首选 GUM 方法假设已识别并校正了所有系统误差。我们回顾了一些处理未校正偏差及其包含在总体不确定度声明中的程序。当偏差及其不确定度被视为与测试结果中的分散无关的计量状态时,可以将参考值的不确定度与偏差的不确定度等同起来。测试结果的标准不确定度是偏差的标准不确定度和测试中测量的标准不确定度的方根和。由于用于估计偏差标准不确定度的公式通常不完整,因此可能存在错误,因此我们提出了一种替代计算方法。接下来,我们提出了一种使用简单算法的图形方法,该方法根据两个概率密度函数的重叠百分比,以测试测量结果与相应参考值之间的差异来量化。我们建议在可能的情况下纠正偏差,并使用图形方法说明这种方法。尽管本评论主要集中在分析化学和医学实验室应用,但其中的许多讨论都适用于计量学的所有领域。

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