Measurement uncertainty estimation

ISO/TS 21748 2004 Guidance for the use of repeatability, reproducibihty and tmeness estimates in measurement uncertainty estimation... 

Ellison, S. L. R., and Barwick, V. J. (1998), Using validation data for ISO measurement uncertainty estimation. Part 1. Principles of an approach using cause and effect analysis, Analyst, 123,1387-1392. 

For nonstandard methods, the standard 17025 lists 11 items required for the procedure. Methods must be validated (see chapter 7) and measurement uncertainty estimated (see chapter 6). In subsection 5.4, reference is made to the control of data, particularly in relation to electronic or automated equipment. 

Just as the value obtained by measurement of a sample carries an uncertainty, so does the laboratory infield realization of the certified value of an RM. If the purpose of the measurement is to validate (Fig. 3) a procedure or instrument calibration, the measurement uncertainty estimated by the laboratory should include the certified value of the RM. If the measurement in the laboratory consists of determining the difference of the value in an unknown with that in an RM, the latter is taken as the reference value. Only when evaluating the uncertainty of the unknown to SI, the RM s certified uncertainty must be combined with that of the inlaboratory measurement of the unknown. 

S, the formulated (spiked) concentration (accompanied by measurement uncertainty estimate) traceable to SI through gravimetric preparation using pure substance chemicals of specified purity... 

Abstract 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 re-... 

Table 2 Method performance and measurement uncertainty estimation. Note that the text is paraphrased for brevity and the numbers in parentheses refer to corresponding items in the EURACHEM guide (column 2)...

Food and feed reference materials (FF-RMs) and especially certified reference materials (CRMs) play an important role in the verification of the accuracy of analytical measurements. They can be used as part of the measurement uncertainty estimation and to assess the trace-ability of the analytical result. CRMs are also used in several cases for the calibration of the instrumental set-up. 

Figure 3.16 is a basic flow chart for the estimation of measurement uncertainty. Estimation of a measurement uncertainty value is a simple process provided the following mles are applied ... 

In some cases it may be useful to make a rough estimation of the measurement uncertainty of a method at the target concentration, for example, at the MRL of a veterinary drug, to help to determine whether the method will be tit for purpose before undertaking a full validation and measurement uncertainty estimation exercise. This can be done by applying the Horwitz formula to obtain an estimate applicable to inter-laboratory reproducibility data, or a suitably adjusted version for intra-laboratory data. " The Horwitz formula, as initially applied to interlaboratory (between-laboratory) reproducibility data R) in percentage, and with the concentration C expressed as a mass fraction, is ... 

Barwick VI, Ellison SLR, Estimating measurement uncertainty using a cause and effect and reconciliation approach. Part 2. Measurement uncertainty estimates compared with collaborative trial expectation. Anal. Commun. 1998 35(ll) 377-383. 

International Standards Organization, ISO 21748, Guidance for the Use of Repeatability, Reproducibility and Trueness Estimates in Measurement Uncertainty Estimation, Geneva, 2004. 

When an analytical laboratory is supplied with a sample and requested to determine the concentrations of one of its constituents, it will doubtless estimate, or perhaps know from experience, the extent of the major random and systematic errors occurring. The customer supplying the sample may well want this information summarized in a single statement, giving the range within which the true concentration is reasonably likely to lie. This range, which should be given with a probability (i.e. it is 95% probable that the concentration lies between. .. and. .. ), is called the uncertainty of the measurement. Uncertainty estimates are now very widely used in analytical chemistry, and are discussed in more detail in Chapter 4. 

Uncertainty expresses the range of possible values that a measurement or result might reasonably be expected to have. Note that this definition of uncertainty is not the same as that for precision. The precision of an analysis, whether reported as a range or a standard deviation, is calculated from experimental data and provides an estimation of indeterminate error affecting measurements. Uncertainty accounts for all errors, both determinate and indeterminate, that might affect our result. Although we always try to correct determinate errors, the correction itself is subject to random effects or indeterminate errors. 

Every measured quantity or component in the main equations, Eqs. (12.30) and (12.31), influence the accuracy of the final flow rate. Usually a brief description of the estimation of the confidence limits is included in each standard. The principles more or less follow those presented earlier in Treatment of Measurement Uncertainties. There are also more comprehensive error estimation procedures available.These usually include, beyond the estimation procedure itself, some basics and worked examples. 

Atmospheric emissions of sulphur dioxide are either measured or estimated at their source and are thus calculated on a provincial or state basis for both Canada and the United States (Figure 2). While much research and debate continues, computer-based simulation models can use this emission information to provide reasonable estimates of how sulphur dioxide and sulphate (the final oxidized form of sulphur dioxide) are transported, transformed, and deposited via atmospheric air masses to selected regions. Such "source-receptor" models are of varying complexity but all are evaluated on their ability to reproduce the measured pattern of sulphate deposition over a network of acid rain monitoring stations across United States and Canada. In a joint effort of the U.S. Environmental Protection Agency and the Canadian Atmospheric Environment Service, eleven linear-chemistry atmospheric models of sulphur deposition were evaluated using data from 1980. It was found that on an annual basis, all but three models were able to simulate the observed deposition patterns within the uncertainty limits of the observations (22). 

In Table 8.1 three different analytical results are listed, the uncertainties of which are estimated in several ways (A) measurement uncertainty only, as sometimes can be done in analytical practice, (B) additionally uncertainty of calibration considered, and (C) uncertainty of sample preparation included (partially nonstatistically estimated). Whereas in cases (A) and (B) the results are judged to be significantly false, in case (C) the difference is statistically not significant. The situation is illustrated in Fig. 8.4a when a comparison is carried out on the basis of the f-test (Eq. 8.6). 

Accuracy is often used to describe the overall doubt about a measurement result. It is made up of contributions from both bias and precision. There are a number of definitions in the Standards dealing with quality of measurements [3-5]. They are only different in the detail. The definition of accuracy in ISO 5725-1 1994, is The closeness of agreement between a test result and the accepted reference value . This means it is only appropriate to use this term when discussing a single result. The term accuracy , when applied to a set of observed values, describes the consequence of a combination of random variations and a common systematic error or bias component. It is preferable to express the quality of a result as its uncertainty, which is an estimate of the range of values within which, with a specified degree of confidence, the true value is estimated to lie. For example, the concentration of cadmium in river water is quoted as 83.2 2.2 nmol l-1 this indicates the interval bracketing the best estimate of the true value. Measurement uncertainty is discussed in detail in Chapter 6. 

Precision estimates are key method performance parameters and are also required in order to carry out other aspects of method validation, such as bias and ruggedness studies. Precision is also a component of measurement uncertainty, as detailed in Chapter 6. The statistics that are applied refer to random variation and therefore it is important that the measurements are made to comply with this requirement, e.g. if change of precision with concentration is being investigated, the samples should be measured in a random order. 

To appreciate why measurement results are not complete without an estimate of the measurement uncertainty. 

All of the standard uncertainty estimates obtained in the previous stage must now be combined to produce an overall uncertainty. Consider a measurement... 

Note that some organizations may not use the terminology used in this book and may not distinguish between SOPs and WIs. Standard Operating Procedures provide details of how a series of operations are carried out. An example of a SOP would be the detailed instruction for carrying out a particular analytical method. Work Instructions give details of how a specific operation is carried out. What might be classed as a WI is how to operate a particular instrument, how to estimate measurement uncertainty or how to calibrate a piece of equipment. 

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