ISO 英文 – INTERNATIONAL STANDARD IS0 TECHNICAL CORRIGENDUM 1 Published ISO Accuracy (Trueness and Precision) of Measurement Methods and Results – Part 5: Alternative Methods for the Determination of the Precision of a. Find the most up-to-date version of ISO at Engineering

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Page 17, Equations 25 and 26 in Subclause 5. Page 38, Equation 72 in Subclause 6. Reference number IS0 A split-level experiment – Determination of protein A design for a heterogeneous material An experiment on a heterogeneous material An application of the general formulae Robust methods for data analysis Robust analysis for a particular level of a uniform-level design Robust analysis for a particular level of a split-level design Robust analysis for a particular level of an experiment on a heterogeneous material Annexes A normative Symbols and abbreviations used in IS0 B informative Derivation of the factors used in algorithms A and S C informative Derivation of equations used for robust analysis The work of preparing International Standards is normally carried out through IS0 technical committees.

Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee. International organisations, governmental and non-governmental, in liaison with ISO, also take pari in the work. Draft International Standards adopted by the technical committees are circulated to the member bodies for voting. IS0 consists of the following parts, under the general title Accuracy trueness and precision of measurement methods and results: General principles and definitions Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method Part 3: Intermediate measures of the precision of a standard measurement method Part 4: Basic methods for the determination of the trueness of a standard measurement method Part 5: Alternative methods for the determination of the precision of a standard measurement method Part 6: Use in practice of accuracy values – – Parts 1 to 6 of IS0 together cancel and replace IS0which has been extended to cover trueness in addition to precision and intermediate precision conditions in addition to repeatability conditions and reproducibilityconditions.

Annex A forms an integral part of this part of IS0 Annexes B, C and D are for information only. Trueness refers to the closeness of agreement between the average value of a large number of test results and the true or accepted reference value.

Precision refers to the closeness of agreement between test results.

This part iwo IS0 should be read in conjunction with IS0 because the underlying definitions and general principles are given there. It gives a basic method for doing this using the uniform-level design. This part of IS0 describes alternative methods to this basic method. When this risk is considered to be serious, the split-level design described in this part of IS0 may be preferred as it reduces this risk.

The basic method requires the preparation of a number of identical samples of the material for use in the experiment. With heterogeneous materials this may not be possible, so that the use of the basic method isso gives estimates of the reproducibility standard deviation that are inflated by the variation between the samples.

### ISO Accuracy of Measurement Methods and Results Package

The design for a heterogeneous material given in this part of IS0 yields information about the variability between samples which is jso obtainable from the basic method; it may be used to calculate an estimate of reproducibilityfrom which the between-sample variation has been removed. The basic method requires tests for outliers to be used to identify data that should be excluded from the calculation of the repeatability and reproducibility standard deviations.

Excluding outliers can sometimes have a large effect on the estimates of repeatability and reproducibility standard deviations, but in practice, when applying the outlier tests, the data analyst may have to use judgement to decide which data to exclude. Alternative methods for the determination of the precision of a standard measurement method 1 Scope This part of I S 0 – provides detailed descriptions of alternatives to the basic method for determining the repeatability and reproducibility standard deviations of a standard measurement method, namely the split-level design and a design for heterogeneous materials; describes the use of robust methods for analysing the results of precision experiments without using isoo tests to exclude data from the calculations, and in particular, the iwo use of one such method.

This part of IS0 complements IS0 by providing alternative designs that may be of more value in some situations than the basic design given in IS0and by providing a robust method of analysis that gives estimates of the repeatability and reproducibility standard deviations that are less dependent on the data analyst’s judgement than those given by the methods described in IS0 At the time of publication, the editions indicated were valid.

All standards are subject to revision, and parties to agreements based on 572-5 part of IS0 are encouraged to investigate the possibility of applying the most recent editions of the standards indicated below. Probability and isso statistical terms. I S 0 Basic method for the determination of repeatability and reproducibiiity of a standard measurement method.

The symbols used in IS0 are given in annex A. With this design there is a risk that an operator may allow the result of a measurement on one sample to influence the result of a subsequent measurement on another sample of the same material. If this happens, the results of the precision experiment willwill be decreased and estimates of the betweenbe distorted: In the split-level design, each participating laboratory is provided laboratory standard deviation c with a sample of each of two similar materials, at each level of the experiment, and the operators are told that the samples are not identical, but they are not told by how much the materials differ.

The split-level design thus provides a method of determining the repeatability and reproducibility standard deviations of a standard measurement method in a way that reduces the risk that a test result obtained on one sample will influence a test result on another sample in the experiment.

## BS ISO 5725-5:1998

An example is given in figure 1. Such graphs can help identify those laboratories that have the largest biases relative to the other laboratories. This is useful when it is possible to investigate the causes of the largest laboratory biases with the aim of taking corrective action.

For example, when the test result is the ixo of an element obtained by chemical analysis, the repeatability and reproducibility standard deviations usually increase as the proportion of the element increases.

It is necessary, for a split-level experiment, that the two sirnilar materials used at a level of the experiment are so simitar that they can be expected to io the same repeatability and reproducibility standard deviations. For the purposes of the split-level design, it is acceptable if the two materials used for a level of the experiment give almost the same level of measurement results, and nothing is to be gained by arranging that they differ substantially.

In many chemical analysis methods, the matrix containing the constituent of interest can influence the precision, so for a split-level experiment two materials with similar matrices are required at each level of the experiment. A sufficiently similar isl can sometimes be prepared by spiking a material with a small addition of the constituent of interest.

When the material is a natural or manufactured product, it can be difficult to find two products that are sufficiently similar for the purposes of a split-level experiment: It should be remembered that the object of choosing the materials for the split-level design is to provide the operators with samples that they do not expect to be identical.

The two samples within a level are denoted U and 6,where a represents a sample of one material, and b represents a sample of the other, similar, material.

The corresponding formulae for the split-level experiment are set out below. To assess the uncertainties of the estimates of the repeatability and reproducibility standard deviations, calculate the following quantities. This is a small difference, so 5752-5 1 and figures B. To assess the uncertainty of the estimate of the bias of the measurement method in a split-level experiment, calculate the quantity A as defined by equation 13 of IS0 Iand use this quantity as described in IS0 To assess the uncertainty of the estimate of a 5752-5 bias in a split-level experiment, calculate the quantity Aas defined by equation 16 of IS0 Oso the number of replicates in a split-level experiment is, in effect, this number of two, it is not possible to reduce the uncertainty of the estimate of laboratory bias by increasing the number of replicates.

If it is necessary to reduce this uncertainty, the uniform-level design should be used instead. The number of replicates, n in IS0may be taken to be the number of split-levels in a split-level design,?. Label the samples so that this is possible, and be careful not to iiso this informationto the participants.

It is stated there that for estimating the accuracy trueness and precision of a measurement method, it is useful to assume that every measurement result is the sum of three components: The lack of a subscript k in B, implies that it is assumed that the bias associated with a laboratory idoes not depend on the material a orb within a level.

This is why it is important that the two materials should be similar. Each combination of a laboratory and 572-55 level gives a “cell” in this table, containing two items of data, yiia and ygb.

Calculate the cell differences Dg.

The method of analysis requires each difference to be calculated in the same sense a-b and the sign of the difference to be retained. Calculate the cell averages yii and enter them into isl table as shown in table 3.

If there are empty cells in table 2, p is now the number of cells in column j of table 2 containing data and the summation is performed over non-empty cells. If there are empty cells in table 3,p is now the number of cells in column j of table 3 containing data and the summation is performed over non-empty cells.

If data are rejected, recalculate the statistics. Table 2 – Recommended form for tabulation of cell differencesfor the split-level design Laboratory 1 1 2 I! To check the consistency of the cell differences, calculate the h statistics as: To show up inconsistent laboratories, plot both sets of these statistics in the order of the levels, but grouped by laboratory, as shown in figures 2 and 3.

The interpretation of these graphs is discussed fully in subclause 7. If a laboratory is achieving generally worse repeatability than the others, then it will show up as having an unusually large number of large h statistics in the graph derived from the cell differences.

If a laboratory is achieving results that are generally biased, then it will show up as having h statistics mostly in one direction on the graph derived from isso cell averages. In either case, the laboratory should be asked to investigate and report their findings back to the 55725-5 of!

To test far stmggiers and outliers in the ce8 Merences, apply Gnibbs’ tests to the values in each column of table 2 in turn.

To test for stragglers and outliers in the cell averages, apply Grubbs’ 57725-5 to the values in each column of table 3 in turn. The interpretation of these tests is discussed fully in subclause 7. They are used to identify results that are so inconsistent with the remainder of the data reported in the experiment that their inclusion in the calculation of the oso and reproducibility standard deviations would affect the values of these statistics substantially.

Usually, data shown to be outliers are excluded from the calculations, and data shown to be stragglers are included, unless there is a good reason for doing otherwise.

If the tests show that a value in one of tables 2 or 3 is to be elirduded from the calculation of the repeatability and reproducibility standard deviations, then the m r e s p m i i n g value in the o h r of these tables should also be excluded from the calculation. A split-level experiment – Determination of protein which involved the determination by combustion of the 4. There were 572-55 participating laboratories, and the experiment contained 14 levels.

W t h cadi, tevet, t w o feeds were used having similar mass fraction of protein in feed. Using equations 8 and 9 in 4. Laboratory 5 gives a point in the bottom left-hand corner of the graph, and Laboratory 1 gives a point in the top right-hand corner: