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Accreditation and Quality Assurance: Journal for Quality, Comparability and Reliability in Chemical Measurement (v.16, #2)
The qualifier “primary” should not be used too lightly in the context of measurement
by Paul De Bièvre (pp. 61-62).
Some metrological aspects of the comparison between two ordinal measuring systems by Emil Bashkansky; Tamar Gadrich; Dafna Knani (pp. 63-72).
The usage of ordinal scales (sometimes called ‘semi-quantitative’ scales) for performing measurements in the area of applied chemical metrology and quality assurance is widespread. This paper presents a method for handling actions such as calibration, measuring systems’ capabilities comparison and reproducibility evaluation as a comparison between two measuring systems (MSs) referring to a known/unknown reference standard. The strength of the agreement between these MSs is evaluated through two known versions of Cohen’s kappa statistics (the traditional one and the modified one). The effectiveness of these statistics from the metrological point of view is examined, and the preferability of the modified kappa statistics is demonstrated via an example.
Keywords: Ordinal scale; Measuring system (MS); Reference standard; Agreement; Cohen’s kappa; Chemical metrology
Soil sampling uncertainty on arable fields estimated from reference sampling and a collaborative trial by U. Kurfürst; U. Buczko; C. Kleimeier; R. O. Kuchenbuch (pp. 73-81).
On three fields of arable land of (3–6)×104 m2, simple reference sampling was performed by taking up to 195 soil increments from each field applying a systematic sampling strategy. From the analytical data reference values for 15 elements were established, which should represent the average analyte mass fraction of the areas. A “point selection standard deviation” was estimated, from which a prediction of the sampling uncertainty was calculated for the application of a standard sampling protocol (X-path across the field, totally 20 increments for a composite sample). Predicted mass fractions and associated uncertainties are compared with the results of a collaborative trial of 18 experienced samplers, who had applied the standard sampling protocol on these fields. In some cases, bias between reference and collaborative values is found. Most of these biases can be explained by analyte heterogeneity across the area, in particular on one field, which was found to be highly heterogeneous for most nutrient elements. The sampling uncertainties estimated from the reference sampling were often somewhat smaller compared to those from the collaborative trial. It is suspected that the influence of sample preparation and the variation due to sampler were responsible for these differences. For the applied sampling protocol, the uncertainty contribution from sampling generally is in the same range as the uncertainty contribution from analysis. From these findings, some conclusions were drawn, especially about the consequences for a sampling protocol, if in routine sampling a demanded “certainty of trueness” for the measurement result should be met.
Keywords: Soil sampling; Sampling uncertainty; Reference sampling; Collaborative trial
On the use of the ‘uncertainty budget’ to detect dominant terms in the evaluation of measurement uncertainty by Manuel Solaguren-Beascoa Fernández (pp. 83-88).
In the evaluation of measurement uncertainty, the uncertainty budget is usually used to identify dominant terms that contribute to the uncertainty of the output estimate. Although a feature of the GUF method, it is also recommended as a qualitative tool in MCM by using ‘nonlinear’ equivalents of uncertainty contributions and sensitivity coefficients. In this paper, the use of ‘linear’ and ‘nonlinear’ parameters is discussed. It is shown that when and only when the standard uncertainty of the output estimate is nearly equal to the square root of the sum of the squares of the individual uncertainty contributions, will the latter be a reliable tool to detect the degree of contribution of each input quantity to the measurand uncertainty.
Keywords: GUM; Monte Carlo Method; Uncertainty; Measurement; Sensitivity coefficient
Application of a special in-house validation procedure for environmental–analytical schemes including a comparison of functions for modelling the repeatability standard deviation by L. Brüggemann; R. Wennrich (pp. 89-97).
For some years, a special in-house validation concept according to the Commission Decision 2002/657/EC of the European Union is employed. The validation concept is based on a variance component model, which allows to consider matrix- and operation-induced deviations and to calculate critical concentrations for given α-errors. The approach relies on a comprehensive mathematical model to asses simultaneously the in-house reproducibility and its components. One important component, the repeatability standard deviation, is estimated by means of a power function of the Horwitz-type. In this study, several performance characteristics were compared based on the use of four recommended estimations for the standard deviation depending on the concentration level of the analyte. A special factorial design for calibration, considering three factors influencing the variance of the measurement values, was applied for the determination of arsenic in surface water samples collected at several abandoned mining sites in Germany. The advantageous applicability of the validation method presented for analytical procedures referring to environmental tasks was demonstrated.
Keywords: In-house validation; Variance component model; Repeatability standard deviation
Key metrological issues in proficiency testing––response to “Metrological compatibility-a key issue in further accreditation” by K. Heydorn by Ilya Kuselman; Ales Fajgelj (pp. 99-102).
A discussion of proficiency testing (PT) topics started by Heydorn (Accred Qual Assur 15:643–645, 2010) is continued in the present paper. The role of PT in the accreditation of testing/analytical laboratories, the use of consensus values (average or weighted average, median, observed standard deviation, etc.) and a metrological background of PT schemes are discussed. It is shown that metrological traceability, comparability, and compatibility, as well as commutability of a reference material, are the key issues of any PT scheme that applies certified reference material as test items. Metrological compatibility of PT results in such schemes is a property demonstrating the closeness of the PT results to the certified value in comparison with the measurement uncertainty of their difference. The metrological background is especially important for the selection and use of PT schemes for a limited number of participants (fewer than 30) as detailed in IUPAC/CITAC Guide on the topic published in 2010 in Pure Appl Chem 82(5):1099–1135.
Keywords: Proficiency testing; Measurement uncertainty; Metrological traceability; Comparability and compatibility; Commutability of a reference material
Measuring with zero measurement uncertainty a primitive quantity
by Xavier Fuentes-Arderiu (pp. 103-103).
‘Verification’ versus ‘validation’: a terminological comparison by René Dybkaer (pp. 105-108).
The present diversity in the definitions and relations of ‘verification’ and ‘validation’ is impractical for such transdisciplinary concepts. General dictionaries, international special language vocabularies and minor lists show that the respective recent formulations by the International Organization for Standardization (ISO) and the Joint Committee for Guides in Metrology (JCGM) are the most quoted. The characteristics of these concepts are elucidated terminologically, and separate concept systems are made for ISO and JCGM to arrive at a preference for a generic rather than an associative relation.
Keywords: Characteristic; Concept system; Terminology work; Validation; Verification
Piotr Koniecczka and Jacek Namieśnik: Quality assurance and quality control in the analytical chemical laboratory: a practical approach
by D. Brynn Hibbert (pp. 109-110).