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Standardization of statistical procedures and evaluation scheme in external quality-control survey

机译:外部质量控制调查中统计程序和评估方案的标准化

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Numerous external quality assessment surveys are being conducted by variety of organizations throughout Japan, but the statistical processing and evaluation scheme are not compatible. Standardization of the procedures is essential to make comparison of results among surveys possible. A coding system is available only for names of analytes and analytical equipments. Systematic coding for analytical principles, manufacturers and standard materials is necessary. Regarding computation of peer-group statistics, the mean and SD are often biased when there are many, or wildly, outlying values. Therefore it is recommended to use an iterative method. The methodology removes a relatively large proportion of the population in the tails of the distribution and re-inflates the SD to compensate for the trimming, thus reaching an unbiased mean and SD by iteration. It is also useful to compute between-method CV and within method-CV by one-way analysis of variance. They represent overall levels of standardization and reproducibility of the analyte, respectively. The evaluation of results is usually based on the peer-group mean and SD. The scheme is unfair for those belonging to a peer-group with a narrow SD. It is recommended to use so-called "common CV evaluation scheme", which is based on a within-method CV computed from overall test results after excluding those peer-groups with large CVs. The common CV is applied to the unbiased peer-group mean to get the evaluation SD. For standardized data processing and statistical analysis, it is crucial to develop a unified, generalized soft ware. We developed its prototype named SurveyMaster I & II and herein introduce their potentials.
机译:日本各地的许多组织都在进行大量外部质量评估调查,但统计处理和评估方案不兼容。程序的标准化对于使调查之间的结果比较成为可能至关重要。编码系统仅适用于分析物和分析设备的名称。必须对分析原理,制造商和标准材料进行系统编码。关于对等组统计信息的计算,当有很多或非常值外的值时,均值和标准差常常会出现偏差。因此,建议使用迭代方法。该方法去除了分布尾部较大比例的总体,并对SD重新充气以补偿修整,从而通过迭代达到无偏均值和SD。通过方差单向分析来计算方法间的CV和方法内的CV也很有用。它们分别代表了分析物的总体标准化水平和可再现性。结果评估通常基于同组平均值和标准差。对于属于SD较窄的对等组的成员,该方案是不公平的。建议使用所谓的“通用CV评估方案”,该方案基于从总体测试结果中计算出的方法内CV,然后将那些具有较大CV的对等组排除在外。将公共CV应用于无偏同组均值以获取评估SD。对于标准化的数据处理和统计分析,开发统一的通用软件至关重要。我们开发了名为SurveyMaster I&II的原型,并在此介绍了它们的潜力。

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