Software support for the Nordtest method of measurement uncertainty evaluation

Software support for the Nordtest method of measurement uncertainty evaluation is described. According to the Nordtest approach, the combined measurement uncertainty is broken down into two main components??the within-laboratory reproducibility (intermediate precision) s _Rw and the uncertainty due to possible laboratory bias u(bias). Both of these can be conveniently estimated from validation and quality control data, thus significantly reducing the need for performing dedicated experiments for estimating detailed uncertainty contributions and thereby making uncertainty estimation easier for routine laboratories. An additional merit of this uncertainty estimation approach is that it reduces the danger of underestimating the uncertainty, which continues to be a problem at routine laboratories. The described software tool??MUkit (measurement uncertainty kit)??fully reflects the versatility of the Nordtest approach: it enables estimating the uncertainty components from different types of data, and the data can be imported using a variety of means such as different laboratory data systems and a dedicated web service as well as manual input. Prior to the development of the MUkit software, a laboratory survey was carried out to identify the needs of laboratories related to uncertainty estimation and other quality assurance procedures, as well as their needs for a practical tool for the calculation of measurement uncertainty.     

A case study in the practical estimation of measurement uncertainty

This case study is written for analytical laboratories, in order to give support to the implementation of the concept of measurement uncertainty for routine measurements. The aim is to provide a practical, understandable and common way of performing measurement uncertainty calculations, based mainly on pre-existing quality control and validation data. Practical examples taken directly from environmental laboratory monitoring are presented and explained. However, the approach is very general and should be applicable to most testing laboratories in the chemical field. Following the protocol of evaluation illustrated in the case study, it is possible to ensure that most relevant uncertainty components associated with the method are covered. Contributions associated with sampling, homogenisation, sub-sampling, and so on, are, however, excluded.     

Proficiency testing in the light of a new rationale in metrology

The novel proposed definition of measurement result in the international metrology vocabulary requires a revision of standards and guidelines for proficiency testing (PT), and a new approach to processing proficiency data is needed to test the ability of laboratories to present not only unbiased quantity values, but reliable estimates of their uncertainty. Hence, an accepted reference value with the smallest possible uncertainty is needed to ascertain the proficiency of laboratories reporting results with lower than average uncertainty. A strategy based on the T-statistic is proposed leading to an accepted reference value that fully reflects the uncertainties reported by participants in a PT scheme and permits calculation of E _n numbers to distinguish whether or not measurement results are consistent with the accepted definition of the measurand. The strategy is applied to PT data from a recent international laboratory intercomparison of uranium isotopic ratios.     

From a single analyzer to multiple instruments—The GUM approach

Assessment and expression of analytical quality have become novel spotlights in medical laboratories since accreditation began in the early 1990s, in Europe. Evaluation of uncertainty of measurement by definition was launched in Finland when the Finnish Accreditation Service (FINAS) accredited the first medical laboratories in the mid 1990s. In spite of all the analytical and statistical knowledge which has been available in medical laboratories for years, evaluation of total uncertainty of measurement has not yet caught on. The concept is still unfamiliar to experts and, indeed, little guidance has been available. National and international activities, with good results, can be shown when the educational aspect is considered. The Guide to the Expression of Uncertainty in Measurement (GUM) remains the main document for uncertainty evaluation. Uncertainty of measurement together with target value of uncertainty can be used as a good measure for analytical quality in large or smaller laboratories over time, because it is a quantitative indication and the evaluation is easy to repeat as running practical tools are available.Presented at the 8th Conference on Quality in the Spotlight, 17–18 March 2003, Antwerp, Belgium     

Uncertainty evaluation in proficiency testing: state-of-the-art, challenges, and perspectives

The evaluation of measurement uncertainty, and that of uncertainty statements of participating laboratories will be a challenge to be met in the coming years. The publication of ISO 17025 has led to the situation that testing laboratories should, to a certain extent, meet the same requirements regarding measurement uncertainty and traceability. As a consequence, proficiency test organizers should deal with the issues measurement uncertainty and traceability as well. Two common statistical models used in proficiency testing are revisited to explore the options to include the evaluation of the measurement uncertainty of the PTRV (proficiency test reference value). Furthermore, the use of this PTRV and its uncertainty estimate for assessing the uncertainty statements of the participants for the two models will be discussed. It is concluded that in analogy to Key Comparisons it is feasible to implement proficiency tests in such a way, that the new requirements can be met. Received: 29 September 2000 Accepted: 3 December 2000     

Estimating measurement uncertainty in an afternoon. A case study in the practical application of measurement uncertainty

The ISO/IEC 17025:1999 standard requires chemical testing laboratories to have an estimate of the uncertainty of their measurements. This is a new requirement for many laboratories and there is confusion as to how to estimate uncertainty. Concerns have been raised about the time and effort required to obtain uncertainty estimates.Uncertainty budgets were prepared for the measurement of benzene, toluene, ethyl benzene and xylenes (BTEX) in water using purge and trap coupled with GC/MS. A time limit of one working afternoon (2 pm–5.30 pm) was imposed for preparing the uncertainty estimate. Details of the uncertainty estimate for toluene are described.The method in question had been in routine use for several years and the laboratory held third party (NATA) accreditation for the test. Consequently a considerable amount of performance data was readily available. Relevant information was extracted from the documented test method, validation data, instrument calibration and from routine quality control. This data was combined according to the principles of the ISO Guide to the Expression of Uncertainty, as promulgated in the Eurachem document "Quantifying Uncertainty in Analytical Measurement."The uncertainty estimates were compared to estimates obtained from generalised empirical models (the Horwitz and Lowthian equations), and from interlaboratory studies of this analysis.A traceability chain from routine measurements to the SI units of metre, kilogram and mole is described.Realistic and useful uncertainty estimates were obtained with a few hours work using data extant in the laboratory.     

Measurement uncertainty in microbiology

Testing laboratories wishing to comply with the requirements of ISO/IEC 17025:1999 need to estimate uncertainty of measurement for their quantitative methods. Many microbiological laboratories have had procedures available for monitoring variability in duplicate results generated by laboratory analysts for some time. These procedures, however, do not necessarily include all possible contributions to uncertainty in the calculations. Procedures for estimating microbiological method uncertainty, based on the Poisson distribution, have been published but, at times, the procedures can either underestimate uncertainty or require laboratories to undertake considerable experimental studies and more complex statistical calculations. This paper proposes procedures for estimating uncertainty of measurement in microbiology, whereby routine laboratory quality control data can be analyzed with simple statistical equations. The approaches used in these procedures are also applied to published data and examples, demonstrating that essentially equivalent results can be obtained with these procedures.     

Measurement uncertainty—Surveys about customers' knowledge, reactions and needs

During discussions early in 2000, representatives of accredited analytical laboratories expressed concern about what the customers' reactions might be when the new requirements for evaluating and reporting uncertainty are implemented. In collaboration with accreditation bodies, authorities, laboratories and interest organisations, a two-page leaflet was produced. It was intended to be used by testing laboratories as information, e.g. together with the test report. To gain further insight into customers' views on measurement uncertainty, two surveys were conducted among some 1,200 Swedish customers. The result shows that the majority of them need and value uncertainty statements in the test report.     

SI-traceable values for cadmium concentration in the water samples of IMEP-6

 The certification measurement for the cadmium concentration in the samples as performed by Isotope Dilution (ID) using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is described in framework of the International Measurement Evaluation Programme (IMEP). By using a primary method of measurement (ID), making up a full uncertainty budget and using a sensitive technique (ICP-MS), reference values traceable to SI can be obtained for this material. The uncertainty budget is performed in accordance with the ISO and EURACHEM guides on uncertainty. A comparison is made with certification results of other experienced laboratories also using primary methods where possible. Received: 8 July 1996/Revised 26 August 1996/Accepted: 1 September 1996     

SI-traceable values for cadmium concentration in the water samples of IMEP-6

 The certification measurement for the cadmium concentration in the samples as performed by Isotope Dilution (ID) using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is described in framework of the International Measurement Evaluation Programme (IMEP). By using a primary method of measurement (ID), making up a full uncertainty budget and using a sensitive technique (ICP-MS), reference values traceable to SI can be obtained for this material. The uncertainty budget is performed in accordance with the ISO and EURACHEM guides on uncertainty. A comparison is made with certification results of other experienced laboratories also using primary methods where possible. Received: 8 July 1996/Revised 26 August 1996/Accepted: 1 September 1996     

Reliability of measurement results in food microbiology: the contribution of reference laboratories in the European Union and of international/European standardization

The contribution of reference laboratories in the European Union and of European/international standardization to the reliability of food microbiology measurement results is discussed. A set of European Union reference laboratories has been established. Each of them coordinates a network of national reference laboratories which, in turn, coordinate networks of laboratories in charge of official testing and sometimes own checks in each European Union country. Their contribution to the reliability of food microbiology measurement results is illustrated by three food safety cases: Listeria monocytogenes, coagulase positive staphylococci and milk/milk products. The contribution of European/international standardization focuses on two topics: method validation and measurement uncertainty. The standards covering these topics—EN ISO 16140 and ISO/TS 19036—are briefly discussed, and an update given on their ongoing revision.     

Uncertainty estimation in organic elemental analysis using information from proficiency tests

We evaluate the uncertainty in organic elemental analysis of C, H, N, and S. We use data from six proficiency tests (PTs), in which some 35 Spanish laboratories participated. The uncertainty of the technique is estimated from the relative within-laboratory and between-laboratory variances for pure substances and samples with complex matrices (soil, powdered milk, oil, ash, and petroleum coke). We also calculate the relative standard uncertainties for individual laboratories when analysing pure substances using historical data from the participation of each laboratory in different editions of PTs. The uncertainty values obtained for the individual laboratories are comparable with the uncertainty of the technique and correlate with the combined z-scores. The evolution over time of those laboratories participating in common editions of PTs is also evaluated.     

Interlaboratory comparison for the determination of five residual organochlorine pesticides in ginseng root samples by gas chromatography

An interlaboratory comparison study for the determination of 5 residual organochlorine pesticides (hexachlorobenzene and 4 hexachlorocyclohexane isomers) in ginseng root was performed. This program [Asia Pacific Laboratory Accreditation Cooperation (APLAC) T049] was the first of its kind for an herbal matrix and involved the participation of 70 laboratories from 26 countries worldwide. Consensus mean values were computed statistically from the reported results, which were eventually used to assess the performance of individual laboratories in terms of the z-scores. The distribution of analytical data was found to be widespread, with standard deviation ranging from 43.9 to 55.9%, and the result patterns obtained were similar to those residue pesticide programs using other matrixes. Although the estimation of measurement uncertainty is a crucial requirement for all quantitative tests for laboratories that meet the requirements of International Organization for Standardization/International Electrotechnical Commisssion (ISO/IEC) 17025, some laboratories in this program had difficulties and showed unfamiliarity with respect to that quality criterion. It was recommended that laboratories review and rectify the situation promptly so that they would have a better understanding of measurement uncertainty or the test service provided.     

Reflections regarding uncertainty of measurement, on the results of a Nordic fatigue test interlaboratory comparison

This paper presents the experiences of calculation and reporting uncertainty of measurement in fatigue testing. Six Nordic laboratories performed fatigue tests on steel specimens. The laboratories also reported their results concerning uncertainty of measurement and how they calculated it. The results show large differences in the way the uncertainties of measurement were calculated and reported. No laboratory included the most significant uncertainty source, bending stress (due to misalignment of the testing machine, incorrect specimens and/or incorrectly mounted specimens), when calculating the uncertainty of measurement. Several laboratories did not calculate the uncertainty of measurement in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM) [1].     

A comparison in the evaluation of measurement uncertainty in analytical chemistry testing between the use of quality control data and a regression analysis

The evaluation of measurement uncertainties has been widely applied to the calibration of measurement instruments, whereas its application to tests, despite increasing requirements, is a more recent phenomenon. The generalization of the evaluation of measurement uncertainties to tests has been a gradual process, in line with changes in the requirements of the normative framework that regulates the accreditation of tests laboratories and also as the perceived good practices have evolved. The sole identification of the relevant sources of uncertainty was followed by the requirement to provide a simplified estimate of the measurement uncertainty, and it is now an accepted requirement to properly evaluate the expanded measurement uncertainty associated with any tests. In this study, the evaluation of measurement uncertainty associated with the determination of sulfate in water will be attempted using a procedure that includes linear regression, with the regression parameters provided with associated uncertainties, and a Monte Carlo method applied as a validation tool of the conventional mainstream evaluation method, concerning the approximations in terms of linearization of the model and the assumed shape of the output distribution introduced by this approach.     

Influence of probability distribution in measurement uncertainty of plane-strain fracture toughness test

Accreditation and Quality Assurance - The evaluation of measurement uncertainty by testing laboratories has a direct impact on the interpretation of the results. In several cases, it is recommended...     

New advances in method validation and measurement uncertainty aimed at improving the quality of chemical data

The implementation of quality systems in analytical laboratories has now, in general, been achieved. While this requirement significantly modified the way that the laboratories were run, it has also improved the quality of the results. The key idea is to use analytical procedures which produce results that fulfil the users needs and actually help when making decisions. This paper presents the implications of quality systems on the conception and development of an analytical procedure. It introduces the concept of the lifecycle of a method as a model that can be used to organize the selection, development, validation and routine application of a method. It underlines the importance of method validation, and presents a recent approach based on the accuracy profile to illustrate how validation must be fully integrated into the basic design of the method. Thanks to the -expectation tolerance interval introduced by Mee (Technometrics (1984) 26(3):251–253), it is possible to unambiguously demonstrate the fitness for purpose of a new method. Remembering that it is also a requirement for accredited laboratories to express the measurement uncertainty, the authors show that uncertainty can be easily related to the trueness and precision of the data collected when building the method accuracy profile.     

On the use of the mean squared error as a proficiency index

The mean squared error is presented as a convenient parameter to be used in assessing laboratories participating in proficiency tests. Its main advantages and disadvantages are presented and compared with the z score and the normalized error. A proficiency index is proposed as the ratio of an estimate of the mean squared error over a reference uncertainty.     

Variances and uncertainties of the sample laboratory-to-laboratory variance (S(L)2) and standard deviation (S(L)) associated with an interlaboratory study

The validation process for an analytical method usually employs an interlaboratory study conducted as a balanced completely randomized model involving a specified number of randomly chosen laboratories, each analyzing a specified number of randomly allocated replicates. For such studies, formulas to obtain approximate unbiased estimates of the variance and uncertainty of the sample laboratory-to-laboratory (lab-to-lab) STD (S(L)) have been developed primarily to account for the uncertainty of S(L) when there is a need to develop an uncertainty budget that includes the uncertainty of S(L). For the sake of completeness on this topic, formulas to estimate the variance and uncertainty of the sample lab-to-lab variance (S(L)2) were also developed. In some cases, it was necessary to derive the formulas based on an approximate distribution for S(L)2.     

Measurement uncertainty – a reliable concept in food analysis and for the use of recovery data?

 Steps which are taken to implement the concept of measurement uncertainty in analytical chemical laboratories should take full account of existing internationally agreed protocols for analytical quality assurance and reflect the needs of particular analytical sectors. For the food sector this may mean that for official purposes the use of the term measurement uncertainty is replaced by the term measurement reliability and that a quantitative estimation of this is made based on existing collaborative trial data. In many analytical sectors, the differing strategies currently followed for the determination and use of recovery information are an important cause of the non-comparability of analytical results. Guidelines which are being prepared for the estimation and use of recovery information in analytical measurement may provide a more unified approach which includes measurement uncertainty as a key concept in the use of recovery data. Received: 4 November 1997 · Accepted: 3 February 1998