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|Author(s):||Chih-Ming Wang; Hariharan K. Iyer;|
|Title:||Detection of influential observation in the determination of the weighted-mean KCRV|
|Published:||January 01, 2005|
|Abstract:||Since the signing of the Mutual Recognition Arrangement, National Metrology Institutes (NMI) have carried out many key comparisons in a wide range of metrological areas to establish the equivalence of their measurement standards. The determination of a key comparison reference value (KCRV) and its associated uncertainty are the central tasks in the evaluation of key comparison data. One of the most popular ways to estimate the KCRV is to use a weighted mean of each NMI's reporting values, with weights inversely proportional to the variances of the NMI's reporting value. One potential problem with the use of the weighted mean is its reliance on the weights that may vary greatly across NMIs. Consequently, some of the NMIs can be influential in the determination of the weighted-mean KCRV. Thus it is of interest to identify the influential NMIs based on some simple and well-defined criteria. In this paper, we present several easy-to-use criteria for detecting influential data in the calculation of the weighted-mean KCRV.|
|Pages:||pp. 262 - 265|
|Keywords:||key comparison,outlier,regression diagnostics|