Multivariate figures of merit

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]. 

A. C. Olivieri, N. M. Faber, J. Ferre, R. Boque, J. H. Kalivas and H. Mark, Uncertainty estimation and figures of merit for multivariate calibration (lUPAC Technical Report), Pure Appl. Chem., 78, 2006, 633-661. 

Practitioners of multivariate calibration typically use different strategies for determining the level of prediction error for a model. Three figures of merit for... 

International Union of Pure and Applied Chemistry, Guidelines for Calibration in Analytical Chemistry. Uncertainty Estimation and Figures of Merit for Multivariate Calibration, 2006. 

The best conditions to operate an axially viewed ICP were set employing experimental designs. The multivariate effect of carrier gas flow and RF power on several analytical figures of merit was studied. Multivariate regression and principal component analysis were used as well to model the system. 

Ohvieri A, Faber NM, Ferre J, Bouque R, Kalivas JH, Mark H. Guidelines for calibration in analytical chemistry. Part 3. Uncertainty estimation of figures of merit for multivariate calibration. Pure Appl Chem 2006 78 633-61. 

Saurina J, Leal C, Compano R, Granados M, Prat MD, Tauler R. Estimation of figures of merit using univariate statistics for quantitative second-order multivariate curve resolution. Anal Chim Acta 2001 432 241-51. 

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