重复测量不确定度的估计:浓度依赖精度情况下的新定量程序

IF 0.8 4区 工程技术 Q4 CHEMISTRY, ANALYTICAL Accreditation and Quality Assurance Pub Date : 2023-10-31 DOI:10.1007/s00769-023-01556-9
Václav Synek, Sylvie Kříženecká
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引用次数: 0

摘要

在许多分析测量中,测试样品中的分析物浓度变化很大。在这种情况下,量化测量不精度的标准偏差(SD)应表示为浓度的函数,c: \({s}_{c}=\sqrt{{\mathrm{s}}_{0}^{2}+{ s}_{r}^{2}{c}^{2}}\),其中so0表示零浓度下的非零SD, sr表示非常高浓度下的近乎恒定的相对SD。在SD重复性的情况下,这些参数可以从常规测试样品上测量的重复结果的差异来估计。具有大量重复结果的数据集可以在内部质量控制中获得。推荐用于此估计的大多数程序都是基于统计要求的加权回归。本文提出了一种统计要求较低的程序。从低至中等浓度和高至中等浓度下测量的重复物的绝对和相对差异的选定子集中估计出了so0和sr参数。估计是通过对差的均方根进行迭代计算得到的,并对第二个参数的影响进行了修正。该程序在蒙特卡罗模拟数据集上进行了验证。该方法获得的参数估计的可变性可能与最佳回归方法获得的估计相似或略差,但优于其他经过测试的回归方法获得的估计的可变性。但是,从不适当的浓度范围中选择重复可能会导致所获得的估计值的变异性大大增加。
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Estimation of uncertainty from duplicate measurements: new quantification procedure in the case of concentration-dependent precision

In many analytical measurements, the analyte concentration in test samples can vary considerably. In such cases, the standard deviation (SD) quantifying measurement imprecision should be expressed as a function of the concentration, c: \({s}_{c}=\sqrt{{\mathrm{s}}_{0}^{2}+{ s}_{r}^{2}{c}^{2}}\), where s0 represents a non-zero SD at zero concentration and sr represents a near-constant relative SD at very high concentrations. In the case of SD repeatability, these parameters can be estimated from the differences of duplicated results measured on routine test samples. Datasets with a high number of duplicate results can be obtained within internal quality control. Most procedures recommended for this estimation are based on statistically demanding weighted regression.

This article proposes a statistically less demanding procedure. The s0 and sr parameters are estimated from selected subsets of absolute and relative differences of duplicates measured at low to medium concentrations and high to medium concentrations, respectively. The estimates are obtained by iterative calculations from the root mean square of the differences with a correction for the influence of the second parameter. This procedure was verified on Monte Carlo simulated datasets. The variability of the parameter estimates obtained by this proposed procedure may be similar or slightly worse than that of the estimates obtained by the best regression procedure, but better than the variability of the estimates obtained by other tested regression procedures. However, a selection of the duplicates from an inappropriate concentration range may cause a substantial increase in variability of the estimates obtained.

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来源期刊
Accreditation and Quality Assurance
Accreditation and Quality Assurance 工程技术-分析化学
CiteScore
1.80
自引率
22.20%
发文量
39
审稿时长
6-12 weeks
期刊介绍: Accreditation and Quality Assurance has established itself as the leading information and discussion forum for all aspects relevant to quality, transparency and reliability of measurement results in chemical and biological sciences. The journal serves the information needs of researchers, practitioners and decision makers dealing with quality assurance and quality management, including the development and application of metrological principles and concepts such as traceability or measurement uncertainty in the following fields: environment, nutrition, consumer protection, geology, metallurgy, pharmacy, forensics, clinical chemistry and laboratory medicine, and microbiology.
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