在方法可重复性不足的情况下评价CRM的同质性:贝叶斯分析与基于方差分析的替代方法的比较

IF 2.5 Q1 Chemistry
Thomas P.J. Linsinger
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引用次数: 1

摘要

方法可重复性不足是标准物质评价的一个问题。在对欧盟委员会联合研究中心(JRC)过去四年发布的36个crm中216个认证参数的同质性研究中,发现在1/3的情况下,方法重复性(sr)过高,无法通过经典方差分析(ANOVA)计算单位间标准差(sbb)。还发现,应用ISO指南35:17中规定的可重复性要求是不可行的,因为它需要不切实际的低可重复性标准偏差或每个单位不可能的高重复次数。采用方差分析(ANOVA)评估均一性不确定度(ubb),同时使用sbb最大值和0、sbb最大值和u * bb、方法重复性隐藏的不确定度、sbb最大值和sbb/√n,以及贝叶斯分析(Bayesian analysis),同时使用信息先验和扩散先验,以及单位均值的标准偏差,使用重复性为1-8%,sbb在0.2和2.8%之间的模拟均一性研究进行比较。研究发现,使用sbb的最大值和sbb/√n作为ubb的估计,可以防止严重低估,但通常会导致对单位间变化的严重高估。使用最大值(sbb, 0)显示最小的平均偏差,但在很大一部分情况下会导致严重低估ubb。使用(sbb, u * bb)极限的最大值,但不能完全消除严重低估的情况。此外,它还会导致平均结果偏向于高值。对于所调查的sbb和sr范围,贝叶斯分析在限制严重低估ubb方面的表现不如max (sbb, u * bb),但限制了对高结果的平均偏差。提出了一种基于风险的方法来处理方法可重复性不足的情况,在评估对认证值的不确定性的其他贡献之后,评估严重高估和低估ubb的影响,并根据此分析选择适当的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluation of CRM homogeneity in cases of insufficient method repeatability: Comparison of Bayesian analysis with substitutes for ANOVA based estimates

Evaluation of CRM homogeneity in cases of insufficient method repeatability: Comparison of Bayesian analysis with substitutes for ANOVA based estimates

Insufficient method repeatability is a problem characterising the evaluation of certified reference materials (CRMs). In investigating the homogeneity studies of 216 certified parameters from 36 CRMs released by the European Commission’s Joint Research Centre (JRC) over the last four years, it was found that in 1/3 of the cases, the method repeatability (sr) was too high to calculate the standard deviation between units (sbb) by classical analysis of variance (ANOVA). It was also found that the application of the repeatability requirement stated in the ISO Guide 35:2017 is not feasible since it would require unrealistically low repeatability standard deviations or an impossibly high number of replicates per unit.

Evaluation of the uncertainty of homogeneity (ubb) as evaluated by ANOVA using both the maximum of sbb and 0, the maximum of sbb and ubb, the uncertainty hidden by method repeatability, the maximum of sbb and sbb/√n and Bayesian analysis, using both informative and diffuse priors, as well as the standard deviation of the unit means, were compared using simulated homogeneity studies with repeatabilities of 1–8% and sbb between 0.2 and 2.8%. It was found that using the maximum of sbb and sbb/√n as an estimate of ubb guards against severe underestimation but usually results in a severe overestimation of the between-unit variation. Using the maximum of (sbb, 0) shows the least average bias but results in a severe underestimation of ubb in a high fraction of cases. Using the maximum of (sbb, ubb) limits, but does not completely eliminate cases of a severe underestimation. Also, it leads to average results biased towards high values. For the range of sbb and sr investigated, Bayesian analysis performed worse than max (sbb, ubb) in limiting severe underestimation of ubb, but limited the average bias towards high results.

A risk-based approach to cases of insufficient method repeatability is proposed where, after evaluating the other contributions to the uncertainty of certified values, the effect of severe over- and underestimation of ubb is evaluated, and an appropriate approach is chosen based on this analysis.

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来源期刊
Analytica Chimica Acta: X
Analytica Chimica Acta: X Chemistry-Analytical Chemistry
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