基于方差分析方法的能力测试解释

IF 0.8 4区 工程技术 Q4 CHEMISTRY, ANALYTICAL
Luiz Henrique da Conceição Leal, Marcelo Lima Alves, Werickson Fortunato de Carvalho Rocha
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引用次数: 0

摘要

能力测试是利用实验室间的比较来评估实验室胜任某一特定测试或测量的能力,并证明所产生结果的可靠性。为了实现这一目标,国际标准ISO 13528:2022提出了四种性能统计数据,其中之一是z分数。一些研究者提出了一种基于方差分析方法的能力测试方案解释的替代方法。本文通过残差分析来选择一个合适的方差分析模型,以便在参与者之间的共识值获得分配值时进行水平测试解释。方差分析方法与z分数进行比较,以评估实验室间比较的性能,以确定车辆排放中存在的氮氧化物量。初步结果表明,两种方法得到的结论不同的一个参与实验室。这种情况的发生是由于违反了使用z分数时未考虑的均方差假设。另一方面,残差分析可以提供这些信息,可行广义最小二乘可以处理异方差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proficiency testing interpretation based on analysis of variance method

Proficiency testing is the use of interlaboratory comparisons to assess the ability of a laboratory to perform a particular test or measurement competently and demonstrate the reliability of the results generated. To achieve this goal, the international standard ISO 13528:2022 presents four performance statistics and one of them is the z score. Some researchers have proposed an alternative approach for proficiency testing scheme interpretation based on an analysis of variance method. This short communication presents residual analysis to choose an appropriate analysis of variance model for proficiency testing interpretation when the assigned value is obtained by consensus value among participants. The analysis of variance approach was compared with z score to assess the performance of interlaboratory comparison for determining the amount of NOx present in vehicle emissions. Preliminary results indicate that the conclusions obtained by both methodologies differ for one of the participating laboratories. This occurs due to violation of the homoscedasticity assumption which is not considered when using the z score. On the other hand, residual analysis can provide such information and feasible generalized least squares can deal with heteroscedasticity .

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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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