posted on 2013-07-02, 00:00authored byE. Rozet, E. Ziemons, R.D. Marini, Ph. Hubert
The
reliability of analytical results obtained with quantitative
analytical methods is highly dependent on the selection of the adequate
model used as the calibration curve. To select the adequate response
function or model the most used and known parameter is to determine
the coefficient R2. However, it is well-known
that it suffers many inconveniences, such as leading to overfitting
the data. A proposed solution is to use the adjusted determination
coefficient Radj2 that aims
at reducing this problem. However, there is another family of criteria
that exists to allow the selection of an adequate model: the information
criteria AIC, AICc, and BIC. These criteria have rarely been used
in analytical chemistry to select the adequate calibration curve.
This works aims at assessing the performance of the statistical information
criteria as well as R2 and Radj2 for the selection of an adequate calibration
curve. They are applied to several analytical methods covering liquid
chromatographic methods, as well as electrophoretic ones involved
in the analysis of active substances in biological fluids or aimed
at quantifying impurities in drug substances. In addition, Monte Carlo
simulations are performed to assess the efficacy of these statistical
criteria to select the adequate calibration curve.