Accuracy Trueness and Precision

As in traditional methods that use univariate calibrations, the description of a method of analysis that uses multivariate calibration must also include the corresponding estimated figures of merit, including accuracy (trueness and precision), selectivity, sensitivity, linearity, limit of detection (LOD), limit of quantification (LOQ) and robustness. In this chapter, only the most common figures of merit are described. For a more extensive review, see [55]. Also, for a practical calculation of figures of merit in an atomic spectroscopic application, see [12]. 

A note of caution is needed here. The figures of merit presented in this section refer to the multivariate calibration model. This multivariate model, built with standards, is then applied to future real samples. If standards and real samples match, as should be the case in most applications, the calibration model is the essential step of the overall analytical procedure. However, if real samples require additional steps (basically preprocessing steps such as extractions, preconcentrations, etc.) different from those of the standards, then the calibration model is just one more step in the whole procedure. If the previous steps are not the same, this means that the figures of merit calculated for the model do not refer to the whole analytical procedure and, therefore, other approaches should be undertaken to calculate them [56]. 

The ISO Guide 3534-1 [57] defines accuracy as the closeness of agreement between a test result and the accepted reference value , with a note stating that the term accuracy, when applied to a set of test results, involves a combination of random components and a common systematic error or bias component . Accuracy is expressed, then, as two components trueness and precision. Trueness is defined as the closeness of agreement between the average value obtained from a large set of test results and an accepted reference value and it is normally expressed in terms of bias. Finally, precision is defined as the closeness of agreement between independent test results obtained under stipulated conditions . 

In multivariate calibration, accuracy reports the closeness of agreement between the reference value and the value found by the calibration model and is generally expressed as the root mean square error of prediction (RMSEP, as described in section 4.5.6) for a set of validation samples  

Bias represents the average difference between predicted and measured p-values for the I, samples in the validation set  

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The reliability of multispecies analysis has to be validated according to the usual criteria selectivity, accuracy (trueness) and precision, confidence and prediction intervals and, calculated from these, multivariate critical values and limits of detection. In multivariate calibration collinearities of variables caused by correlated concentrations in calibration samples should be avoided. Therefore, the composition of the calibration mixtures should not be varied randomly but by principles of experimental design (Deming and Morgan [1993] Morgan [1991]). 

Accuracy (Trueness and Precision) of Measurement Methods and Results - Part 1. General Principles and Definitions , ISO 5725-1 1994, International Organization for Standardization (ISO), Geneva, Switzerland 1994. 

International Organization for Standardization (ISO), Statistical methods for quality control, Vol. 2, 4th Edition, Accuracy (trueness and precision) of measurement methods and results - Part 2 Basic method for the determination of repeatability and reproducibility of a standard measurement method, ISO 1994(E), 5725-2. 

International organization for Standardization, Accuracy (trueness and precision) of measurement methods and results, ISO/DIS 5725-1 to 5725-3, Draft versions 1990/91. 

Includes all information on analytical quality control, such a precision clauses (repeatability and reproducibility data), table of statistical data outlining accuracy (trueness and precision) of method... 

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. 

ISO 5725-5 1998 Accuracy (trueness and precision) of measurement methods and results—Part 5 alternative methods for the determination of the precision of a standard measurement method ISO 5725-6 1994 Accuracy (trueness and precision) of measurement methods and results—Part 6 use in practice of accuracy values. http //www.iso.org/iso/search.htm qt=5725 published= on active tab=standards... 

ISO, 1994, International Standard ISO 5725 "Accuracy (trueness and precision) of measurement method and results", 1994-12. 

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