Trueness tests

Even if most examples and procedures presented apply to in-house validation, the procedure does not distinguish between validations conducted in a single laboratory and those carried out within inter-laboratory method performance studies. A preference for inter-laboratory studies can be concluded from the statement that laboratories should always give priority to methods which have been tested in method performance studies. Within the procedure a profound overview of different categories of analytical methods according to the available documentation and previous external validation is given. For example, if a method is externally validated in a method performance study, it should be tested for trueness and precision only. On the other hand, a full validation is recommended for those methods which are published in the scientific literature without complete presentation of essential performance characteristics (Table 9). 

Trueness. Absence of systematic errors can be tested traditionally by means of recovery functions see Sect. 6.1.2, Fig. 6.3C Burns et al. [2002]. For this reason the concentration estimated by the model, x, is compared with the true concentration value, xtrue, by a regression model... 

Measurements are subject to systematic errors as well as the random errors covered in Section 4.3.2. Bias is the difference between the mean value of a large number of test results and an accepted reference value for the test material. The bias is a measure of trueness of the method. It can be expressed in a number of ways, i.e. simply as a difference or as a ratio of the observed value to the accepted value. This latter representation, when expressed as a percentage, is often termed recovery. This represents how much of the analyte of interest has been extracted from the matrix and measured. This is dealt with in Section 4.6.3. 

Trueness Closeness of agreement between the average value obtained from a large series of test results and an accepted reference value. Trueness is normally expressed in terms of bias. 

II the difference approach, which typically utilises 2-sided statistical tests (Hartmann et al., 1998), using either the null hypothesis (H0) or the alternative hypothesis (Hi). The evaluation of the method s bias (trueness) is determined by assessing the 95% confidence intervals (Cl) of the overall average bias compared to the 0% relative bias value (or 100% recovery). If the Cl brackets the 0% bias then the trueness that the method generates acceptable data is accepted, otherwise it is rejected. For precision measurements, if the Cl brackets the maximum RSDp at each concentration level of the validation standards then the method is acceptable. Typically, RSDn> is set at <3% (Bouabidi et al., 2010),... 

Limit of Quantification (LoQ) is the lowest concentration of analyte in a sample that can be determined with acceptable accnracy, i.e. with acceptable precision and acceptable trueness, nnder the stated conditions of the test. 

Method validation seeks to quantify the likely accuracy of results by assessing both systematic and random effects on results. The properly related to systematic errors is the trueness, i.e. the closeness of agreement between the average value obtained from a large set of test results and an accepted reference value. The properly related to random errors is precision, i.e. the closeness of agreement between independent test results obtained under stipulated conditions. Accnracy is therefore, normally studied as tmeness and precision. 

International Organization for Standardization, Draft International Standard ISO/DIS 5725-3, Accuracy (trueness and precision) of measurements methods and results. Part 3 Intermediate measures on the precision of a test method, 1991. 

Results aimed at Precision multiple results, both repeatability and reproducibility >%RSD is compared to theoretical Horwitz Horrat values Trueness Single result per test material, > calculation of Z score as measure for bias... 

Anklam et al. [7] as well as Ahmed [8] recently published a comprehensive overview of different PCR assays that have been published in the literature. The authors tried to include performance data adding to the value of the review articles. The validation of PCR methods and thus the establishment of such performance criteria is still the subject of much debate. H bner et al. [9] suggested an approach for the validation of PCR assays. In general, it is currently the view of most researchers that validation of a PCR assay should not differ essentially from the validation of other analytical methods. Thus, all principles outlined in the ISO standard 17025 General requirements for the competence of testing and calibration laboratories, ISO standard 5725 Accuracy (trueness and precision) of measurement methods and results as well as the principles as laid down by Codex Alimentarius (http //www.co-dexalimentarius.net), are applicable to PCR. 

Accuracy means the closeness of agreement between a test result and the accepted reference value. It is determined by determining trueness and precision [57], In a strict sense, the accuracy of a method is affected by systematic (bias) as well as random (precision) error components, but the term is often used to describe only the systematic error component, i.e., in the sense of bias. In this sense sometimes... 

Meeting stringent performance characteristics for each analyte (in particular test accuracy, including both precision of the measurement and trueness of the measurement), and... 

ISO uses two terms, trueness and precision , to describe the accuracy of a measured value. 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 of test results, or in other words the variability between repeated tests. The standard deviation of the measured value obtained by repeated determinations under the same conditions is used as a measure of the precision of the measurement procedure. The repeatability limit r (an intra-laboratory parameter) and the reproducibility limit R (an inter-laboratory parameter) are calculated as measures of precision. Again, precision and trueness together describe the accuracy of an analytical method. 

This is a procedure that is regularly given more importance than deserved in the efforts to guarantee the trueness of experimental results when determining trace elements in foodstuffs. The information value of recovery tests in element analysis by AAS in food is very limited. Recovery information is important in chemical analysis where there is an extraction step in order to elucidate the efficiency of... 

The accuracy of liquid-handling operations in HTS is analyzed by three key parameters derived from test experiments in which equal volume aliquots are pipetted or dispensed over the plate. The trueness over the plate is a measure of the deviation of the average of the actual volume dispensed over a plate from the intended volume. It is measured gravimetrically and is defined as... 

Reference materials, that is, materials of known composition of components (usually determined on the basis of interlaboratory tests), can be of great help in proper preparation of standard solutions. They usually serve for verification of trueness of a given analytical procedure and accuracy of the obtained analytical result. If the composition of a reference material matches that of the analyzed sample, and the substance to be analyzed is one of its components, then the material can be utilized for calibration in such a way that a series of standard solutions is prepared via addition of analyte in known quantities. 

According to ISO, bias is the difference between the expectation of the test results and an accepted reference value [17]. It may consist of more than one systematic error component. Bias can be measured as a percent deviation from the accepted reference value. The term trueness expresses the deviation of the mean value of a large series of measurements from the accepted reference value. It can be expressed in terms of bias. 

Abstract A protocol has been developed illustrating the link between validation experiments, such as precision, trueness and ruggedness testing, and measurement uncertainty evaluation. By planning validation experiments with uncertainty estimation in mind, uncertainty budgets can be obtained from validation data with little additional effort. The main stages in the uncertainty estimation process are described, and the use of true-... 

Key words Measurement uncertainty Method validation Precision Trueness Ruggedness testing... 

We have applied this protocol to the evaluation of the measurement uncertainty for a method for the determination of three markers (Cl solvent red 24, Cl solvent yellow 124 and quinizarin (1,4-dihydroxyanthra-quinone)) in road fuel. The method requires the extraction of the markers from the sample matrix by solid phase extraction, followed by quantification by HPLC with diode array detection. The uncertainty evaluation involved four experimental studies which were also required as part of the method validation. The studies were precision, trueness (evaluated via the analysis of spiked samples) and ruggedness tests of the extraction and HPLC stages. The experiments and uncertainty calculations are described in detail in Part 2. A summary of the uncertainty budget for the method is presented in Fig. 3. 

In Part 1 [1] we described a protocol for the evaluation of measurement uncertainty from validation studies such as precision, trueness and ruggedness testing. In this paper we illustrate the application of the protocol to a method developed for the determination of the dyes Cl solvent red 24 and Cl solvent yellow 124, and the chemical marker quinizarin (1,4-dihydroxyanthra-quinone) in road fuel. The analysis of road fuel samples suspected of containing rebated kerosene or rebated gas oil is required as the use of rebated fuels as road fuels or extenders to road fuels is illegal. To prevent illegal use of rebated fuels, HM Customs and Excise require them to be marked. This is achieved by adding solvent red 24, solvent yellow 124 and quinizarin to the fuel. A method for the quantitation of the markers was developed in this laboratory [2]. Over a period of time the method had been adapted to improve its performance and now required re-validation and an uncertainty estimate. This paper describes the experiments under-... 

So, the methods characteristic of each test, comprising taken together a type of tests, must undergo validation testing of their results. This is the implementation of the method, and the establishment of a standard for its performance. For the standardization of quantitative methods, this consists at a minimum of a determination of trueness when blank utilization, certified reference materials (or reference materials, or spiking materials) or collaborative trials are used, repeatability (r) with repetition,... 

In evaluation of the performance characteristics of a candidate method, precision, accuracy (trueness), analytical range, detection limit, and analytical specificity are of prime importance. The sections in this chapter on method evaluation and comparison contain a detailed outline of these concepts and their assessment. The estimated performance parameters for a method can then be related to quality goals that ensure acceptable medical use of the test results (see section on Analytical Goals), From a practical point of view, the ruggedness of the method in routine use is of importance. Reliable performance when used by different operators and with different batches of reagents over longer time periods is essential. 

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