Statistical Tests and Validation of Calibration

A calibration procedure has to be validated with regard to general and specific requirements under which the calibration model has been developed. For this purpose, it is important to test whether the conditions represented in Fig. 6.6 are fulfilled. On the other hand, it is to assure by experimental studies that certain performance features (accuracy, precision, sensitivity, selectivity, specificity, linearity, working range, limits of detection and of quantification, robustness, and ruggedness, see Chap. 7) fulfil the expected requirements. 

The underlying calibration procedure of a newly developed analytical method has to be examined by basic validation studies to determine the reliability of the method and its efficiency in comparison with traditional methods. In order to ensure long-term stability, it is necessary to perform revalidations, which can be combined with the use of quality control charts, over meaningful time periods. 

Regarding calibration, it is of special importance to characterize the following features  

Commercial software packages are usually able to represent graphically the residual errors (deviations) of a given calibration model which can be examined visually. Typical plots as shown in Fig. 6.8 may give information on the character of the residuals and therefore on the tests that have to be carried out, such as randomness, normality, linearity, homoscedasticity, etc. 

Accuracy. In general, the accuracy of analytical results is assured by recovery studies (Wegscheider [1996] Danzer [1995] Burns et al. [2002]). According to the recovery function in the general three-dimensional calibration model (see Fig. 6.3), common studies on systematic deviations (Fig. 4.3), and Eqs. (4.2) and (4.3) the following recovery formulae 

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