Discussion Forum

Accreditation and Quality Assurance

, Volume 14, Issue 10, pp 553-563

First online:

Laboratory effects models for interlaboratory comparisons

  • Blaza TomanAffiliated withStatistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology, U.S. Department of Commerce Email author 
  • , Antonio PossoloAffiliated withStatistical Engineering Division, Information Technology Laboratory, National Institute of Standards and Technology, U.S. Department of Commerce

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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.

Keywords

Reference value Consistent subset Degrees of equivalence Statistical model Fixed effect Random effects Bias