ISO uncertainty and collaborative trial data

 The possibility of using interlaboratory study repeatability and reproducibility estimates as the basis for measurement uncertainty estimates is discussed. It is argued that collaborative trial reproducibility is an appropriate basis for estimating uncertainty in routine testing provided certain conditions are met by the laboratory. The primary shortcomings relate to establishment of traceability and consequent estimation of bias associated with the method, and quantitatively establishing the relevance to the single laboratory. Approaches to resolving both difficulties are proposed, the former via full implementation of trueness determination suggested in ISO 5725 : 1994 or by independent checks on individual accuracy and precision, the latter via a reconciliation procedure. The paper also discusses other factors including sampling and sample pre-treatment, change in sample matrix, and the influence of level of analyte. Received: 28 October 1997 · Accepted: 17 November 1997     

Uncertainty from sampling: workshop to launch a Nordtest handbook on sampling uncertainty estimation and control

A workshop on uncertainty in sampling was held in Hillerød, Denmark, on 12–13 April 2007 to launch a new handbook on sampling quality assurance and uncertainty estimation. The participants of the workshop were approximately 60 delegates from 15 European countries, representing institutions performing sampling, users of the data, research institutions, as well as accreditation bodies. Materials from the workshop, including examples, tools, and calculation aids for the work can be found at http://www.samplersguide.com. The Nordtest handbook Uncertainty from sampling will be made available on the Nordtest web site at http://www.nordicinnovation.net/nordtest.cfm under NT technical reports, report number NT tec 604. Until the final report is available on the Nordtest web site, an advance draft of the Nordtest handbook is available from http://www.samplersguide.com.     

Determination of uncertainty in analytical measurements from collaborative study results on the analysis of a phenoxymethylpenicillin sample

The correct interpretation of a measurement result requires knowledge about its uncertainty. Depending on the conditions under which the analyst is operating, different operational definitions of uncertainty have been proposed. They include: within-laboratory uncertainty, reproducibility uncertainty, bias-included uncertainty and absolute uncertainty. Here we consider the evaluation of the reproducibility uncertainty derived from the results obtained in an inter-laboratory experiment. Nine laboratories participated in an inter-laboratory study for the analysis of phenoxymethylpenicillin. The analyses consisted of a Karl-Fischer water determination, an acid-base titration to assay phenoxymethylpenicillin and a liquid chromatography (LC) method to determine 4-hydroxyphenoxymethylpenicillin and other impurities. The experimental set-up allowed to obtain for each determination s_r² and s_L² as estimates of the repeatability variance (σ_r²) and the between-laboratory variance (σ_L²), respectively. The reproducibility uncertainties for the different assays were then derived from these estimates.     

Combined uncertainty factor for sampling and analysis

Accreditation and Quality Assurance - Measurement uncertainty that arises from primary sampling can be expressed as an uncertainty factor, which recognises its sometimes approximately log-normal...     

Modifying uncertainty from sampling to achieve fitness for purpose: a case study on nitrate in lettuce

Existing methods have been applied to estimate the uncertainty of measurement, caused by both sampling and analysis, and fitness-for-purpose of these measurements. A new approach has been taken to modify the measurement uncertainty by changing the contribution made by the sampling process. A case study on nitrate in lettuce has been used to demonstrate the applicability of this new generic approach. The sampling theory of Gy was used to predict the alterations in the sampling protocol required to achieve the necessary change in sampling uncertainty. An experimental application of this altered sampling protocol demonstrated that the predicted change in sampling uncertainty was achieved in practice. For the lettuce case study, this approach showed that composite samples containing 40 heads, rather than the usual ten heads, produced measurements of nitrate that where more fit-for-purpose.     

Improved evaluation of measurement uncertainty from sampling by inclusion of between-sampler bias using sampling proficiency testing

A realistic estimate of the uncertainty of a measurement result is essential for its reliable interpretation. Recent methods for such estimation include the contribution to uncertainty from the sampling process, but they only include the random and not the systematic effects. Sampling Proficiency Tests (SPTs) have been used previously to assess the performance of samplers, but the results can also be used to evaluate measurement uncertainty, including the systematic effects. A new SPT conducted on the determination of moisture in fresh butter is used to exemplify how SPT results can be used not only to score samplers but also to estimate uncertainty. The comparison between uncertainty evaluated within- and between-samplers is used to demonstrate that sampling bias is causing the estimates of expanded relative uncertainty to rise by over a factor of two (from 0.39% to 0.87%) in this case. General criteria are given for the experimental design and the sampling target that are required to apply this approach to measurements on any material.     

Measurement uncertainty and the use of reference materials

The use of (certified) reference materials and quality control materials can form a suitable basis for evaluating measurement uncertainty of routine measurements. In particular when these materials are used for quality control purposes, it is not always evident how the quality control data can be used in the uncertainty budget of a routine measurement. Current guidance documents on the evaluation of measurement uncertainty and the use of reference materials treat this subject only in part, or in very generic terms. ISO/REMCO has established a new working group that will provide practical guidance and examples on how to use quality control data in the evaluation of measurement uncertainty. A short introduction to the subject is given.

Cost effective, robust estimation of measurement uncertainty from sampling using unbalanced ANOVA

There is an increasing appreciation that the uncertainty in environmental measurements is vitally important for their reliable interpretation. However, the adoption of methods to estimate this uncertainty has been limited by the extra cost of implementation. One method that can be used to estimate the random components of uncertainty in the sampling and analytical processes requires the collection of duplicate samples at 10% of the primary sampling locations and duplicating the analyses of these samples. A new program has been written and applied to a modified experimental design to enable a 33% reduction in the cost of analysing this 10% subset, whilst accommodating outlying values. This unbalanced robust analysis of variance (U-RANOVA) uses an unbalanced rather than the balanced experimental design usually employed. Simulation techniques have been used to validate the results of the program, by comparison of the results between the proposed unbalanced and the established balanced designs. Comparisons are also made against the seed parameters (mean and standard deviation) used to simulate the parent population, prior to the addition of a proportion (up to 10%) of outlying values. Application to a large number of different simulated populations shows that U-RANOVA produces results that are effectively indistinguishable from the results produced by the accepted balanced approach and are equally close to the true (seed) parameters of the parent normal population.     

Setting up a decision rule from estimated uncertainty: emission limit value for PCDD and PCDF incineration plants in Wallonia, Belgium

Complex analytical procedures are often required to prove the non-compliance with a specific legislation. In the case of a small overlap of the limit, integration of the method uncertainty in the decision-making process is essential. The decision rule proposed in Wallonia, Belgium, for the non-compliance of waste incineration plants with the EU limit value for PCDD and PCDF emissions is presented. The method uncertainty was estimated annually over 6 years from duplicate measurements using two top-down approaches. Depending on the congener, the standard uncertainty varies from 30 to 85%, with a good correlation between calculations. The analytical contribution was estimated using a bottom-up evaluation. The impact of the sampling step was deduced from the whole estimation and represents more than 80% of the total uncertainty budget. No optimisation is foreseen at this time because of practical field constraints. Based on the average fraction of each congener, the uncertainty associated with the measurement result has been established and shows a high stability over the years. Using this value, a guard band has been calculated and will be proposed to the regulatory body. Presented at the Measurement Uncertainty Symposium, Berlin, Germany, April 2008.     

Correction to: Combined uncertainty factor for sampling and analysis

Accreditation and Quality Assurance - In the penultimate paragraph of the original publication, a confidence interval of 93 mg/kg to 971 mg/kg was reported. These values should be...     

Calibration and uncertainty assessment for certified reference gas mixtures

The weighted least squares method to build an analysis function described in ISO 6143, Gas analysis—Comparison methods for determining and checking the composition of calibration gas mixtures, is modified to take into account the typically small number of instrumental readings that are obtained for each primary standard gas mixture used in calibration. The theoretical basis for this modification is explained, and its superior performance is illustrated in a simulation study built around a concrete example, using real data. The corresponding uncertainty assessment is obtained by application of a Monte Carlo method consistent with the guidance in the Supplement 1 to the Guide to the expression of uncertainty in measurement, which avoids the need for two successive applications of the linearizing approximation of the conventional method for uncertainty propagation. The three main steps that NIST currently uses to certify a reference gas mixture (homogeneity study, calibration, and assignment of value and uncertainty assessment), are described and illustrated using data pertaining to an actual standard reference material.     

Effects of external electromagnetic fields on the conformational sampling of a short alanine peptide

Non‐equilibrium molecular dynamics simulations of a solvated 21‐residue polyalanine (A21) peptide, featuring a high propensity for helix formation, have been performed at 300 K and 1 bar in the presence of external electromagnetic (e/m) fields in the microwave region (2.45 GHz) and an r.m.s. electric field intensity range of 0.01–0.05 V/Å. To investigate how the field presence affects transitions between the conformational states of a protein, we report 16 independent 40 ns‐trajectories of A21 starting from both extended and fully folded states. We observe folding‐behavior of the peptide consistent with prior simulation and experimental studies. The peptide displays a natural tendency to form stable elements of secondary structure which are stabilized by tertiary interactions with proximate regions of the peptide. Consistent with our earlier work, the presence of external e/m fields disrupts this behavior, involving a mechanism of localized dipolar alignment which serves to enhance intra‐protein perturbations in hydrogen bonds (English, et al., J. Chem. Phys. 2010 , 133, 091105), leading to more frequent transitions between shorter‐lifetime states. © 2012 Wiley Periodicals, Inc.     

Appropriate rather than representative sampling, based on acceptable levels of uncertainty

Appropriate sampling, that includes the estimation of measurement uncertainty, is proposed in preference to representative sampling without estimation of overall measurement quality. To fulfil this purpose the uncertainty estimate must include contribution from all sources, including the primary sampling, sample preparation and chemical analysis. It must also include contributions from systematic errors, such as sampling bias, rather than from random errors alone. Case studies are used to illustrate the feasibility of this approach and to show its advantages for improved reliability of interpretation of the measurements. Measurements with a high level of uncertainty (e.g. 50%) can be shown to be fit for some specified purposes using this approach. Once reliable estimates of the uncertainty are available, then a probabilistic interpretation of results can be made. This allows financial aspects to be considered in deciding upon what constitutes an acceptable level of uncertainty. In many practical situations ”representative” sampling is never fully achieved. This approach recognises this and instead, provides reliable estimates of the uncertainty around the concentration values that imperfect appropriate sampling causes. Received: 28 December 2001 Accepted: 25 April 2002     

Discussion on homogeneity assessment of reference materials based on uncertainty comparison method

Accreditation and Quality Assurance - An uncertainty comparison method is proposed to assess the homogeneity of reference materials. The method compares “standard uncertainty associated with...     

Measurement uncertainty and its implications for collaborative study method validation and method performance parameters

ISO principles of measurement uncertainty estimation are compared with protocols for method development and validation by collaborative trial and concomitant "top-down" estimation of uncertainty. It is shown that there is substantial commonality between the two procedures. In particular, both require a careful consideration and study of the main effects on the result. Most of the information required to evaluate measurement uncertainty is therefore gathered during the method development and validation process. However, the information is not generally published in sufficient detail at present; recommendations are accordingly made for future reporting of the data.     

Compliance with legal requirements: definition of limits, sampling and measurement uncertainty

In many cases compositional requirements for foodstuffs (e.g. limits for the fat, protein, dry matter, or water content) are established by legislation. Adequate compliance testing is possible only if limits are clearly defined, taking measurement and sampling uncertainty into consideration. Furthermore, decisions on compliance must be based on samples which reflect the composition of the quantity to be evaluated. The resulting sample sizes are normally regarded by food inspection authorities as being much larger than acceptable. Consequently, an alternative strategy should be developed. Autocontrol data (i.e. inspection results obtained by the factory) in principle provide an adequate data basis for decisions on compliance. However, they must be reliable and the food inspection authority must have access to these data on request. Using these data and on condition that they show an approximate normal distribution, an inspection strategy based on arithmetic mean and standard deviation can be developed. Reliable and transparent decisions on compliance can thus be made. In many cases an adequate verification of food authenticity requires a comparison of raw material and product composition. Maximum acceptable differences, taking the relevant sources of variation into consideration, have to be defined and should be used instead of limits. Received: 17 April 2002 Accepted: 23 June 2002     

Design of experiment for evaluation of uncertainty from sampling in the framework of the fitness for purpose concept: a case study

The design of an experiment for the evaluation of sampling uncertainty in the framework of the fitness for purpose concept is described in terms of probabilities (risks of the user) of type 1 and type 2 errors in decisions concerning the significance of effects influencing the sampling uncertainty and the measurement results. As a case study, an experiment based on the duplicate method for quantification of the sampling uncertainty and inhomogeneity (heterogeneity) of a melt of tin-free bronze produced in a 10-ton reflective oven is analyzed. The melt is defined as the sampling target. It is shown that the number of such targets (melts), the number of samples under analysis and the number of replicate analyses can be minimized, i.e., the size and cost of the experiment can be reduced, if the user knows which risks are acceptable. When inhomogeneity of the sampling target has a systematic character, like the decrease of the mass fraction of aluminum from the beginning to the end of the melt pouring in the case study, the inhomogeneity effect can be separated from the sampling uncertainty and evaluated according to the user’s needs.     

The uncertainty of a result from a linear calibration

The standard error of a result obtained from a straight line calibration is given by a well known ISO-endorsed expression. Its derivation and use are explained and the approach is extended for any function that is linear in the coefficients, with an example of a weighted quadratic calibration in ICPAES. When calculating the standard error of an estimate, if QC data is available it is recommended to use the repeatability of the instrumental response, rather than the standard error of the regression, in the equation.