Methods for evaluating data from key comparisons are examined and the existing methods for evaluating inconsistent data are briefly characterized. A practical approach is proposed for evaluating inconsistent data.
Similar content being viewed by others
References
BIPM 1999, Mutual Recognition of National Measurement Standards and of Calibration and Measurement Certificates Issued by National Metrology Institutes (MRA).
M. G. Cox, “The evaluation of key comparison data,” Metrologia, 39, 589–595 (2002).
ISO/IEC Guide 99:2007, International Vocabulary of Metrology – Basic and General Concepts and Associated Terms (VIM).
CIPM MRA-D-05, Measurement Comparisons in the CIPM MRA, www.bipm.org, accessed Nov. 28, 2012.
K. Weise and W. Woger, “Removing model and data nonconformity in measurement evaluation,” Meas. Sci. Technol., 11, 1649–1658 (2000).
R. Willink, “Statistical determination of a comparison reference value using hidden errors,” Metrologia, 39, 343–354 (2002).
L. Nielsen, “Identification and handling of discrepant measurements in key comparisons,” Izmer. Tekhn., No. 5, 63–68 (2003); Measur. Techn., 46, No. 5, 513–522 (2003).
D. R. White, “On the analysis of measurement comparisons,” Metrologia, 41, 122–131 (2004).
R. Kacker, “Combining information from interlaboratory evaluations using a random effects model,” ibid., 132–136.
C. M. Sutton, “Analysis and linking of international measurement comparisons,” ibid., 272–277.
M. G. Cox, “The evaluation of key comparison data: determining the largest consistent subset,” Metrologia, 44, 187–200 (2007).
I. Lira, “Combining inconsistent data from interlaboratory comparisons,” ibid., 415–421.
E. Elster and B. Toman, “Analysis of key comparisons: estimating laboratories’ biases by a fixed effects model using Bayesian model averaging,” Metrologia, 47, 113–119 (2010).
B. Toman and A. Possolo, “Laboratory effects models for interlaboratory comparisons,” Accredit. Quality Assur., 14, 553–563 (2009).
O. Bodnar et al., “Application of Bayesian model averaging using a fixed effects model with linear drift for the analysis of key comparison CCM.P-K12,” Izmer. Tekhn., No. 6, 7–11 (2013); Measur. Techn., 56, No. 6, 584–590 (2013).
Author information
Authors and Affiliations
Corresponding author
Additional information
Here we offer our readers the last of a selection of articles based on material from the sixth international seminar “Mathematical, statistical, and computer support of the quality of measurements” held in St. Petersburg at the Mendeleev All-Russia Research Institute of Metrology (VNIIM) in June 2012. The first of this group of articles was published in the April 2013 issue (No. 4) of Measurement Techniques.
Translated from Izmeritel’naya Tekhnika, No. 6, pp. 3–7, June, 2013.
Rights and permissions
About this article
Cite this article
Chunovkina, A.G., Burmistrova, N.A. & Zvyagin, N.D. An approach for evaluating the results of key comparisons of standards with inconsistent data. Meas Tech 56, 577–583 (2013). https://doi.org/10.1007/s11018-013-0248-4
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11018-013-0248-4