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Accreditation and Quality Assurance: Journal for Quality, Comparability and Reliability in Chemical Measurement (v.14, #10)
Manufacturing a chain logically starts with manufacturing the first link, thus is logically started a metrological traceability chain
by Paul De Bièvre (pp. 517-519).
The quality of pH measurements 100 years after its definition by M. Filomena Camões (pp. 521-523).
Analytical chemistry is a scientific discipline based on the search of qualitative and quantitative information embodied in unknown samples which are representative of targeted systems. A. Lavoisier measured masses, S. Arrhenius discovered ions, namely hydrogen ions, S. Sørensen introduced pH and the chemical community has been dealing abundantly with them, first in the frame of classical analysis and later by means of instrumental methods of analysis responsible for large amount of data. Although statistical treatment of measurement results became part of the procedures, it took a few decades of thinking and globalization of the economy to realize that more was needed for the sake of evidence of quality; and this was found in the bases of the science of measurement and on the metrological approach. At the dawn of the twenty-first century, the most measured chemical parameter, pH, set the example of such hierarchical targeting of measurement results fit for a certain purpose, which is worth noticing particularly because 100 years have elapsed since its first definition and initial recommendation of the measurement procedure.
Keywords: Analytical chemistry; Quality; Metrology; pH; Centenary
Use of prediction equations for reviewing measurement results in the clinical laboratory by María José Castro-Castro; Beatriz Candás-Estébanez; Gemma Solé-Enrech; Xavier Fuentes-Arderiu (pp. 525-528).
In the clinical laboratory, one of the most objective ways to perform the final review of measurement results is the use of the so-called plausibility control (i.e., set of procedures used to decide if a measurement result is valid or not according to established clinical and biological criteria). The present study is focused on the estimation of several prediction equations derived from pairs of biological quantities having a pathophysiological relationship and statistically correlated to detect objectively doubtful results in the context of plausibility control. These prediction intervals, that may be used alone or combined with other procedures involved in the plausibility control, are a very useful tool for the improvement of the final review of the laboratory results.
Keywords: Plausibility control; Validation of results; Prediction interval
Validation of a method for the determination of short-chain chlorinated paraffins in soil and sediments by F. Pellizzato; Marina Ricci; A. Held; H. Emons (pp. 529-540).
An alternative approach for the reliable quantification of short-chain chlorinated paraffins (SCCPs) in sediment and soil, based on the existing method of carbon skeleton gas chromatography is presented. The method is proposed to establish an operationally defined measurand. The number of analytes to be looked at is notably reduced and the calibration problems encountered with the electron capture negative ionisation detection overcome because the conversion efficiency and the response are largely independent on the chlorine content of SCCPs. The accurate quantification is facilitated by the availability of n-alkanes as pure standards for calibration. To achieve the comparable results between laboratories, this method should be standardised. The first steps of this process, in-house development and full validation in sediment and soil, are presented for the first time. The limit of detection and quantification of 1.1 and 3.5 nmol g−1, respectively, repeatability of 5% and relative expanded uncertainty of 12% were achieved providing a routinely applicable method for a reliable quantification of SCCPs.
Keywords: SCCPs; Polychlorinated n-alkanes; Carbon skeleton method; Method validation; Soil; Sediment; Method-defined parameter; Standardisation
Consideration concerning interlaboratory test for cement in the last 20 years by Graziela Virginia Guslicov; Mariana Coarna; Alice Pop; Cristina Vlad; Nicoleta Vlad (pp. 541-546).
Since 1988, over 40 laboratories representing research institutes, cement plants, pre-cast units, hydro plant construction companies, industrial construction companies, building companies, etc. from nine countries—Romania, Republic of Moldova, Croatia, Serbia, Macedonia, Bulgaria, Hungary, Ukraine and Lebanon—take part every year in an interlaboratory test organized by our laboratory. The subject of the interlaboratory test for cement was 37 laboratory tests: 12 chemical determinations, 7 physical tests and 9 mechanical tests carried out with 2 types of sand, from CEPROCIM and from each participant laboratory. The paper presents the evolution of two statistical parameters (standard deviation of reproducibility and/or coefficient of variation) for a period of 20 years and for 11 laboratory tests. The results strongly prove that interlaboratory test is one of the most efficient tools to establish a common language for all the participant laboratories performing cement testing procedures.
Keywords: Interlaboratory test; Coefficient of variation; Standard deviation of reproducibility; Efficiency
Towards standardization of external quality assessment schemes by using bias values based on biological variation by Abdurrahman Coskun; Ibrahim Unsal; Mustafa Serteser; Arno Fraterman (pp. 547-552).
The precision and trueness of current instruments and methods in clinical laboratories is much better than in the past. However, the z-score and other comparison variables that are currently used in external quality assessment programs are based on relative data. Thus, they may change from program to program and also change over time within the same program and consequently may not be useful or cost-effective. We therefore devised a test-specific decision limit for accepting or rejecting test results based on a combination of the data of within- and between-subject biological variations. We then applied these limits to a group of tests performed in our laboratory and compared our results with those of external quality assessment programs. In addition, we combined external and internal quality control data on the same graph and prepared a two-dimensional graph for different levels of control sera. Inspection of all results of control sera on this new graph was more useful for decision making. We concluded that the z-score is not reliable for comparisons of test results in external quality assessment. As a substitute for this currently accepted practice, we assert that control limits based on biological variation are more reliable, and can be useful in the evaluation of both external and internal quality assessments and their combination on this new graph.
Keywords: Analytical variation; Biological variation; Bias; Coefficient of variation; External quality assessment; z-score
Laboratory effects models for interlaboratory comparisons by Blaza Toman; Antonio Possolo (pp. 553-563).
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
Laboratory effects models for interlaboratory comparisons by Blaza Toman; Antonio Possolo (pp. 553-563).
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
A measurement: a concert? by Nineta Majcen (pp. 565-566).
The article describes the importance of calibration of all the instruments that are used in a certain measurement procedure as well as different ways of their calibration. As to bring the topic closer to the users of measurements, analogy with an orchestra is used.
Keywords: Calibration; Measurements in physics; Measurements in chemistry; Orchestra concert
Metrology infrastructure for sustainable development of the Americas: the role of SIM by Humberto S. Brandi; Taynah Lopes de Souza (pp. 567-573).
Reliable measurements are essential to guarantee all aspects required for the sustainable development of nations. There is an increasing awareness of the need to discuss, compare and improve infrastructures in the context of global economic efficiency, and market access for goods and services for both developed and developing countries. This is where metrology, standardization and conformity assessment come in. In order to further develop these activities, countries have been organizing themselves into regional cooperation groups. The Inter-American Metrology System (SIM) brings together the National Metrology Institutes of all 34 OAS member countries, aiming at the further development of a sound metrological basis, what lays in the basis of the technical infrastructure necessary for the sustainable development. In this paper the goals and objectives of SIM and some of its main projects will be analyzed, emphasizing the initiatives of chemical metrology and of quality management systems in the region.
Keywords: Metrology infrastructure; Sustainable development; SIM; Chemical metrology; Quality management systems