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Robust Algorithm S to assess the precision of interlaboratory measurements

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The application of robust statistical methods to assess the precision (uncertainty) of the results of interlaboratory comparison tests is presented. The case, when these results may include outliers is considered. An usual rejection of such data reduces the reliability of evaluation, especially for small samples. The robust methods take into consideration all samples data including outliers. The use of the robust method Algorithm S is provided for estimating the precision of some measuring method tested in comparative studies in the group of accredited laboratories. Result obtained for simulated example is very close to the case with rejection outliers, but more reliable.
Wydawca
Rocznik
Strony
111--114
Opis fizyczny
Bibliogr. 18 poz., rys., tab., wykr., wzory
Twórcy
  • National Technical University of Ukraine "KPI", Chair of Automation of Experimental Studies, Kiev, Ukraine
autor
  • Industrial Research Institute of Automation and Measurement (PIAP), Warszawa, Poland
autor
  • National Aviation University, Department of Biocybernetics and Aerospace Medicine, Kiev, Ukraine
  • Bialystok University of Technology, Faculty of Electrical Engineering, Bialystok, Poland
Bibliografia
  • [1] ISO/IEC 17025:2005 General requirements for the competence of testing and calibration laboratories.
  • [2] ISO/TR 10017:2003 Guidance on statistical techniques for ISO 9001:2000.
  • [3] ISO/IEC Guide 99:2010 - International Vocabulary of Metrology.
  • [4] ISO 10012:2004 - Measurement management systems - Requirements for measurement processes and measuring equipment.
  • [5] Guide to the Expression of Uncertainty in Measurement.GUM. First ed. 1993 ISO Switzerland, last corrected ed. JCGM BIPM, 2008.
  • [6] Tukey J. W.: Exploratory Data Analysis, Addison-Wesley, 1978.
  • [7] Willinik R., What is robustness in data analysis. Metrologia 45, pp. 442-447, 2008.
  • [8] Huber P. J., Ronchetti E. M., Robust Statistics 2nd edition. Wiley, 2011.
  • [9] Farrant T. J.: Practical statistics for the analytical scientist: A bench guide. Royal Society of Chemistry, 1997.
  • [10] Rosario P., Martínez J.L., Silván J.M.: Comparison of different statistical methods for evaluation of proficiency test data. Accreditation and Quality Assurance, vol. 13, issue 9, pp. 493-499, 2008, doi: 10.1007/s00769-008-0413-7.
  • [11] Wilrich P. T.: The determination of precision of qualitative measurement methods by interlaboratory experiments, Accreditation and Quality Assurance, vol. 15, issue 8, pp. 439-444, 2010, doi: 10.1007/s00769-010-0661-1.
  • [12] Coucke W., China B., Delattre I., Lenga Y., Van Blerk M, Van Campenhout C., Van de Walle P., Vernelen K., Albert A.: Comparison of different approaches to evaluate external quality assessment data. Clinica Chimica Acta, vol. 413, no 5-6, pp. 582, 2012, doi:10.1016/j.cca.2011.11.030.
  • [13] Volodarsky, E. T., Warsza, Z. L.: Application of two robust methods on the example of inter-laboratory comparison. In: Pavese, F., Bremser, W., Chunovkina, A.G., Fischer, N., Forbes, A.B. (eds.) Advanced Mathematical and Computational Tools in Metrology and Testing X. Series on Advances in Mathematics for Applied Sciences volume 86, World Scientific Publishing Company, pp. 385-391, 2015.
  • [14] ISO 5725-2, -5: 2002 Accuracy (trueness and precision) of measurement methods and results – Part 2: basic method for the determination of repeatability and reproducibility of a standard measurement method - Part 5: Alternative methods for the determination of the precision of standard measurement methods. International Standardization Organization, Geneva, Switzerland.
  • [15] ISO 13528:2005 Statistical methods for use in proficiency testing by inter-laboratory comparisons (IDT), attachment C2.
  • [16] Zieliński R.: Tablice statystyczne (Statistical Tables). PWN Warszawa, (1972) (or any other statistical tables, also in internet).
  • [17] Lemeshko B. Yu., Lemeshko S. B., Gorbunova A. A.: Application and power of criteria for testing the homogeneity of variances Part I Parametric criteria. Measurement Techniques, vol. 53, issue 3, pp. 237-246, 2010, doi: 10.1007/s11018-010-9489-7.
  • [18] Volodarsky E., Warsza Z.: Zastosowanie statystyki odpornościowej na przykładzie badań międzylaboratoryjnych. Przegląd Elektrotechniczny - Electrical Review. Vol. 11, pp. 260–267, 2013.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8e127741-0d01-4570-9ab3-b4786205dd51
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