Consistency tests for key comparison data
Consistency tests for key comparison data
复制标题
关键对比数据一致性检验
DOI：
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发表时间：
2004
期刊：
影响因子：
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通讯作者：
D. F. Vecchia
中科院分区：
文献类型：
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作者：
H. Iyer;Chih;D. F. Vecchia
国家计量标准国际比对结果为国际计量委员会（CIPM）制定的相互承认安排（MRA）提供了技术基础。由于许多关键比较已经完成，一些新的关键比较实验目前正在进行，我们现在对成功分析关键比较数据和对结果作出适当解释所需解决的统计问题有了更好的了解。显然，需要一种系统的方法来对关键比较数据进行统计分析，并由所有参与实验室进行常规分析。关键比较参考值（KCRV）及其相关不确定度和等效度的确定是关键比较数据评价的中心任务。然而，KCRV的令人满意的定义是基于这样的假设：所有实验室都在估计共同循环伪影的相同未知量，即不同实验室的结果相互一致。在本文中，我们比较了一些检验一致性假设的统计方法。
Results of International Key Comparisons of National Measurement Standards provide the technical basis for the Mutual Recognition Arrangement (MRA) formulated by Le Comite International des Poids et Mesures (CIPM). With many key comparisons already completed and a number of new key comparison experiments currently under way, we now have a better understanding of the statistical issues that need to be addressed for successfully analysing data from key comparisons and making proper interpretations of the results. There is clearly a need for a systematic approach to statistical analyses of key comparison data that can be implemented routinely by all participating laboratories.The determination of a key comparison reference value (KCRV) and its associated uncertainty and the degrees of equivalence are the central tasks in the evaluation of key comparison data. A satisfactory definition of a KCRV, however, is based on the assumption that all laboratories are estimating the same unknown quantity of the common circulating artefact, that is, the results from the different laboratories are mutually consistent. In this paper, we compare a number of statistical procedures for testing the consistency assumption.