Assessment of goodness-of-fit for the main analytical calibration models: Guidelines and case studies
This critical review paper will discuss the main analytical calibration models as well as the guidelines for their practical use. The main models used to fit a multiple-point calibration dataset are: 1) linear unweighted or ordinary least squares regression (OLSR); 2) quadratic unweighted least squa...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/247394 |
| Acceso en línea: | http://hdl.handle.net/10261/247394 |
| Access Level: | acceso abierto |
| Palabra clave: | Back-calculated concentration Calibration Determination coefficient Goodness-of-fit Least squares regression Linear regression Quadratic regression Relative error Weighted regression |
| Sumario: | This critical review paper will discuss the main analytical calibration models as well as the guidelines for their practical use. The main models used to fit a multiple-point calibration dataset are: 1) linear unweighted or ordinary least squares regression (OLSR); 2) quadratic unweighted least squares regression (QLSR); 3) linear weighted least squares regression (WLSR). Unfortunately, there is no standard procedure in analytical chemistry for objectively testing the goodness-of-fit of calibration models. Different proposals were reported in the literature. However, none is more commonly used, and probably not more controversial than R2. In this document, a three step simple calibration diagnosis has been proposed. It is based on a combination of different procedures such as graphical plots, statistical significance tests and numerical parameters. Experimental conditions and design of calibration procedures are very relevant for appropriate selection. Finally, some information on the choice of the different models will be reported in four case studies. |
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