Abstract
The statistical analysis of results from inter-laboratory comparisons (for example Key Comparisons, or Supplemental Comparisons) produces an estimate of the measurand (reference value) and statements of equivalence of the results from the participating laboratories. Methods to estimate the reference value have been proposed that rest on the idea of finding a so-called consistent subset of laboratories, that is, eliminating allegedly outlying participants. We propose an alternative statistical model that accommodates all participant data and incorporates the dispersion of the measurement values obtained by different laboratories into the total uncertainty of the various estimates. This model recognizes the fact that the dispersion of values between laboratories often is substantially larger than the measurement uncertainties provided by the participating laboratories. We illustrate the methods on data from key comparison CCQM–K25.
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Acknowledgments
The authors are grateful to Paul De Bièvre for his interest in a discussion of laboratory effects models in the context of a CCQM Key Comparison, and also wish to express their appreciation for the many useful comments that Michele Schantz, Will Guthrie, Hung-kung Liu, and Nien-fan Zhang (all from NIST) made on an early draft of this contribution.
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An erratum to this article is available at http://dx.doi.org/10.1007/s00769-010-0707-4.
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Toman, B., Possolo, A. Laboratory effects models for interlaboratory comparisons. Accred Qual Assur 14, 553–563 (2009). https://doi.org/10.1007/s00769-009-0547-2
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DOI: https://doi.org/10.1007/s00769-009-0547-2