Iso guide expression uncertainty measurement gum

Because the intermediate precision study is carried out for the entire analytical assay at the validation stage, individual contributions to the intermediate precision here, weighting intermediate precision cannot be taken into account for avoiding redundant counting of uncertainty.

Thus, the uncertainty of mass will include the uncertainty contribution of lack of linearity of balance, the uncertainty due to temperature effect and the calibration uncertainty. Kadis pointed out [ 10 ], the evaluation of uncertainty of volumetric measurements consists of three kinds of contributions: specification limits for the glassware of a given class, repeatability of filling the glassware to the mark and temperature effects.

Again, in order to avoid double counting and uncertainty redundancy, the precision of filling the flask is not considered here; thus, the uncertainty in the volume measurement is given by. Generally, in routine analysis, analytical determinations involve instrumental method where indirect calibration is applied. Common scenarios include external calibration, standard addition calibration in case of matrix effects and internal standard calibration when intrinsic analytical signal variations appear or analyte losses may occur owing to sample preparation procedures [ 11 ].

In case of linear calibration, the calibration straight line is established by preparing calibration standards. The primary stock standard solution is made by weighing the suitable mass of standard m std , of a given purity P in the corresponding volume of solvent V s.

But this concentration has an uncertainty derived from the uncertainty in the weighting, in its purity and in the uncertainty of the glassware. The working standard solutions are prepared by diluting a volume V i of the stock standard solution to a final volume V f. So, the concentration of any calibration standard is given by. In our case, the independent variable is the concentration of standard C i and the Y variable is the analytical signal. The unknown analyte content is predicted from interpolation of the sample response signal Y 0 according to.

Aside from the calibration uncertainty, an additional uncertainty contribution can be considered from the preparation of standards as indicated in Eq. Thus, the uncertainty of concentration is given by the uncertainty on sample analyte concentration coming from calibration, and the uncertainty due to the preparation of standards. Intralaboratory assessment of method accuracy encompasses both precision and trueness study.

Intermediate precision is the intralaboratory global precision under varied conditions as expected within a laboratory in a future assay. Both precision and trueness studies have to be carried out at least at three analyte concentration levels low, medium and high in order to cover the full range of analyte concentration indicated in the method scope.

In his excellent paper, Kadis [ 13 ] discussed the double counting risk in the uncertainty budget when calibration uncertainty is considered together with the precision uncertainty. Accordingly, the first term under the radical in Eq. Moreover, the recovery uncertainty includes the precision of the analyte mean value, which is used in the computation of recovery.

Thus, some authors do not include the precision uncertainty together with the recovery uncertainty in the budget [ 13 ]. The use of cause and effect diagrams for designing the uncertainty budget including the in-house validation data is illustrated in the following worked example selected as case study. Solutions that contain quinine in acid medium 0. The determination of quinine in tonic water samples is carried out according to the following procedure [ 16 ]: 1 mL of tonic water previously degassed by 15 min sonication in an ultrasonic bath was pipetted into a mL volumetric flask and dilute to the mark with 0.

The fluorescence intensity of this solution is measured in a fluorescence spectrometer in 10 mm pathway quartz cells at nm excitation wavelength and at nm emission wavelength. The quinine concentration is interpolated in the corresponding calibration curve. Recovery and precision data are taken from the in-house validation study of the method. The corresponding cause and effect Ishikawa diagram is depicted in Figure 1.

Cause and effect diagram for the fluorimetric determination of quinine in tonic water. In order to establish the corresponding calibration curve, a stock solution of quinine was prepared by weighing Six working standards solution covering from 0. The fluorescence intensity of each working standard at nm excitation wavelength and at nm emission wavelength was measured in triplicate.

The results are shown in Table 1. Fluorescence intensities UA for the five working standard solutions, measured in triplicate. Fluorescence intensities show a linear behavior against the quinine concentration according to a calibration straight line with a correlation coefficient of about 0. Uncertainty due to preparation of working calibration standards is computed from Eq.

The uncertainty of the standard mass can be evaluated according to Eq. In our case, the balance specifications were: Linearity a L : 0. Sensitivity temperature coefficient a T : 2. Thus, we have:. The uncertainty of purity is evaluated from the specification: 0. Uncertainty in volumes from pipettes or volumetric flasks are calculated from Eq. The corresponding tolerances for glassware laboratory Class A are gathered in Table 2 , except for the class A graduated pipette of 1 mL for delivering volumes from 0.

Accordingly, we get. The total relative uncertainty of the working standards can be evaluated by avoiding multiple counting as follows:. The uncertainties of the assay and sample volume are also estimated from Eq. Both precision and trueness study was performed by predicting the actual concentrations of the three spiked placebos according to the recommended fluorimetric procedure for quinine determination.

Measurements were made on 5 days for each validation standard with three replications of the assay. The results obtained are presented in Table 3. The best way to estimate both the uncertainty contribution of intermediate precision and the recovery or bias of the analytical assay when validation standards are available, is using ANOVA at a given concentration of the validation standard, namely T , considering p different conditions 5 days in this case and n replications 3 days in this case.

These data are presented in Table 4. A significance test has been used to evaluate if the recovery is significantly different from unity for each spiked placebo:. Relative precision and uncertainty of recovery for the three validation standards in the fluorimetric determination of quinine in tonic water. As can be seen in Eq. Now, all contributions of specification factors have been included in the budget. Consider now that a sample of tonic water Schweppes has been analyzed by following the recommended procedure.

Accordingly, the value of calibration uncertainty from Eq. The concentration of quinine in the sample according Eq. Then, by applying Eq. Emphasis is stressed on reviews and taking into account the high number of references available, the authors apologize for those they may have overlooked or inadvertently omitted. Selected applications about the estimation of uncertainty in volumetric glassware, analytical balance and calibration curves, as well as the evaluation of the measurement uncertainty in classical and instrumental techniques are shown in Tables 6 and 7.

Figure 2 shows the number of publications cited per year, whereas in Figure 3 , the number of paper cited by journal for the most cited journals appears. Selected papers about the estimation of uncertainty in volumetric glassware, analytical balance and calibration curves. Selected papers on evaluation of the measurement uncertainty in classical and instrumental techniques.

Number of publications cited per year. Number of papers cited by journals. Uncertainty is a measure of the quality of a measurement. It is of vital importance in many sectors of analytical chemistry to introduce quality control and quality assurance in production, complying with and enforcing laws and regulations; calibrating standards and instruments or developing and comparing international and national reference standards among others.

However, from an analytical viewpoint, this approach is sometimes tedious, time-consuming and unrealistic. One way to overcome these limitations is the procedure for evaluating uncertainty of analytical assays in routine analysis using the GUM approach together with the data from in-house validation based on the cause and effect diagram coming from the analytical specification function. Expressions to calculate the different contributions of uncertainty have to be carefully adapted in order to avoid double counting.

The procedure is illustrated with a case study on fluorimetric determination of quinine in tonic water showing that it is very suitable for evaluating the uncertainty of the analyte content of future samples in routine analysis.

Finally, a summary including modern reviews on the estimation of measurement uncertainty of analytical assays by GUM is outlined in tabular form, which can be a useful guide for those interested in the subject. Moreover, selected application ranging from volumetric glassware, analytical balance, calibration curves, as well as the evaluation of the measurement uncertainty in classical and instrumental techniques in a wide variety of fields are given.

Graphs on the number of references cited over per year and the number of papers by most cited journals are also included. Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.

Help us write another book on this subject and reach those readers. Login to your personal dashboard for more detailed statistics on your publications. Edited by Gaffar Sarwar Zaman.

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. Downloaded: Introduction The quality of analytical results is crucial because future decisions will be based on them. Uncertainty of sample mass In a typical mass determination, the analytical balance is zeroed with the empty container on the pan, and the container is the filled and weighed.

Uncertainty of glassware volume As R. Uncertainty of concentration coming from calibration Generally, in routine analysis, analytical determinations involve instrumental method where indirect calibration is applied.

Uncertainty of the analytical assay from the in-house data of method validation precision and trueness Intralaboratory assessment of method accuracy encompasses both precision and trueness study. Again, according to EURACHEM [ 2 ], the trueness bias study can be performed by repeated analysis of a certified reference materials CRM , using the complete measurement procedure; by comparing the results of analyzed samples against a reference method; and by applying recovery assays, using spiked placebos validation standards when available or spiked samples instead, and evaluating the recovery.

Thus, an estimation of the uncertainty of bias or recovery is calculated. Uncertainty coming from calibration and standards In order to establish the corresponding calibration curve, a stock solution of quinine was prepared by weighing Table 1. Table 2.

Uncertainty of assay and sample volumes The uncertainties of the assay and sample volume are also estimated from Eq. Class A glassware. Table 3. Tolerances for class A laboratory glassware. Table 4. Content Authors Ref. General overview about concepts, models, methods, and computations that are commonly used for the evaluation of measurement uncertainty, and their application in realistic examples drawn from multiple areas of science and technology. Possolo and Iyer, [ 19 ] A complete procedure to encompass an uncorrected bias into the expanded uncertainty with a fixed coverage probability.

Synek, [ 20 ] Reported scientific uncertainties by analyzing 41, measurements of quantities from medicine, nuclear and particle physics, and interlaboratory comparisons ranging from chemistry to toxicology.

Bailey, [ 21 ] The GUM revision: the Bayesian view toward the expression of measurement uncertainty. Stant et al. Willink, [ 25 ] A new way to express uncertainty of measurement is proposed that allows for the fact that the distribution of values attributed to the measurand is sometimes approximately lognormal and therefore asymmetric around the measurement value. Ramsey and Ellison, [ 26 ] Revision of the GUM: reasons why the Guide needed a revision, and why that revision could not go in a direction different from the one that it has been taken.

Bich, [ 27 ] Validating the applicability of the GUM procedure. Cox and Harris, [ 28 ] Evolution in thinking and its impact on the terminology that accompanied the development of the GUM Ehrlich, [ 29 ] The developments in uncertainty concepts and practices that led to the third edition of the Eurachem Guide on uncertainty evaluation. Ellison, [ 30 ] A review of monte carlo simulation using microsoft excel for the calculation of uncertainties through functional relationships, including uncertainties in empirically derived constants.

The importance of reporting calibration results in a compact way that is easily propagated down the traceability chain is also discussed. Nielsen, [ 32 ] Overview about statistical models and computation to evaluate measurement uncertainty. Possolo, [ 33 ] Discussion about recent situation in measurement science, and how to obtain a reliable measurement result using the expression of metrological traceability together with measurement uncertainty.

Imai, [ 34 ] A new strategy for the analytical validation based on the uncertainty profile as a graphical decision-making tool, and to exemplify a novel method to estimate the measurement uncertainty.

Saffaj et al. Chew et al. Farrance and Frenkel, [ 37 ] Estimation of the measurement uncertainty in quantitative determination of ketamine and norketamine in urine using a one-point calibration method. Ma et al. Contains a selection of the contributed papers at this workshop and show how the evaluation of uncertainty is now being applied to a wide range of analyses.

Williams, [ 39 ] Highlight some of the differences between the two concepts of total error and uncertainty but also to stress their main similarities. Rozet et al. Iwaki, [ 41 ] Managing quality vs. Westward, [ 42 ] Comparison of the approach to measure uncertainties proposed in ISO and GUM from a statistician point of view. Deldossi and Zappa, [ 43 ] Utilizing the correlations between the N individual results, an equation is derived to combine the N individual uncertainties of N measurements.

Using the newly derived equation including the correlation coefficient, three measurement uncertainties of three measurement results are combined as an example. Nam et al. Priel, [ 45 ] Critical debate about the revision of the Guide to the expression of uncertainty in measurement.

Bich, [ 46 ] Course aimed at developing understanding of measurement and uncertainty in the introductory physics laboratory. The course materials, in the form of a student workbook, are based on the probabilistic framework for measurement as recommended by the International Organization for Standardization in their publication GUM.

Buffler et al. Kadis, [ 48 ] Treatment of uncorrected measurement bias in uncertainty estimation for chemical measurements. Magnusson and Ellison, [ 49 ] A critical overview of the current doubtful practice on presentation of correlated data in the physics literature and in the scientific and technological databases.

Ezhela, [ 50 ] A detailed step-by-step guide to analytical method validation, considering the most relevant procedures for checking the quality parameters of analytical methods. Kacher et al. Meyer, [ 52 ] Critical review about calibration-, uncertainty-, and recovery-related documents from 10 consensus-based organizations. Bich et al. Dimech et al. Gregory et al. The propagation of distributions as the best way to evaluate the measurement. Uncertainty and the use of Monte-Carlo method for performing the propagation of distributions is outlined and discussed.

Herrador et al. Kacker et al. White and Farrance, [ 63 ] Approach to determine the overall uncertainty by combining the uncertainties of the individual results when the difference is statistically significant by GUM. Choi et al. Kristiansen, [ 65 ] Critique of the Guide to the expression of uncertainty in measurement method of estimating and reporting uncertainty in diagnostic assays.

Krouwer, [ 66 ] Effect of non-significant proportional bias in the final measurement uncertainty. Maroto et al. Kessel, [ 68 ] Operational definitions of uncertainty taking into account the differences in the ways in which truth, uncertainty and error are conceived. Hund et al. It is addressed primarily to the bodies that will be responsible for the introduction of uncertainty into routine practice.

AMC, [ 71 ] Future trends in analytical quality assurance, the evaluation of the quality of analytical results by estimation of their uncertainties. The present state-of-the-art is described, and the impact caused by the declaration of uncertainties in chemical results is foreseen.

Cortez, [ 72 ] Critical reflexion about the uncertainty concept and its method for estimation. Thompson, [ 73 ] Guidelines for evaluating and expressing the uncertainty of NIST measurement results.

Taylor and Kuyatt, [ 74 ]. Table 5. Content Reference Ref. Volumetric glassware Uncertainty on using graduated volumetric glassware for the concentration of samples concentration tube and its effect on measurement accuracy.

Matsuda et al. Mukund et al. Technical specification of an analytical balance such as: readability, repeatability, linearity, off-center loading and hysteresis and for volumetric glassware: repeatability, readability, temperature coefficient of sensitivity, temperature scattering, meniscus reading and environmental conditions temperature and humidity are considered. Rahman et al. Proof sent to secretariat or FDIS ballot initiated: 8 weeks. Close of voting.

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