Proficiency testing with ordinal categorical data
Proficiency testing with ordinal categorical data
复制标题
使用序数分类数据进行熟练程度测试
DOI：
10.1142/9789811242380_0025
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
and Jun-ichi Takeshita
中科院分区：
文献类型：
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作者：
Tomomichi Suzuki;Momoko Isono;and Jun-ichi Takeshita
能力验证是通过总结和比较测量结果来评估参与实验室的表现。本文讨论了有序分类数据的测量方法。从是否适用于能力验证程序的角度出发，对有序分类数据统计显著性检验的三种方法进行了详细的探讨。这些方法包括：Taguchi提出的累积检验、Takeuchi和Hirotsu提出的累积卡方检验以及Bashkansky、Gadrich和Kuselman提出的ORDANOVA。我们的研究结果表明，ORDANOVA方法是适用于能力测试，并提出了一个程序，使用这些统计量来分析能力测试与有序分类数据。
Proficiency testing is carried out to evaluate the performance of participating laboratories by summarizing and comparing the measurement results. This paper discusses methodologies related to measurements with ordinal categorical data. It investigates in detail three methods of statistical significance test with ordinal categorical data, from the viewpoint of whether they can be applied to proficiency testing procedures. These methods are: the cumulative test proposed by Taguchi, the cumulative chi-square test proposed by Takeuchi and Hirotsu, and ORDANOVA proposed by Bashkansky, Gadrich, and Kuselman. Our results suggest that the ORDANOVA method is applicable to proficiency testing and proposes a procedure using these statistics to analyze proficiency testing with ordinal categorical data.