Comparison of selected retention models in reversed-phase liquid chromatography

Retention models are usually compared by how well the model equation fits r etention data for one solute taken over a range of mobile phase composition s. Even when retention data for multiple solutes are used, the quality of t he fit is often judged by the statistical goodness-of-fit alone, This study compared four different RPLC retention models, encompassing three distinct mathematical forms. Each model was fit to the retention data of multiple s olutes and the sets of best-fit parameters were examined in terms of the un derlying physico-chemical assumptions of the models. Next, for the linear a nd quadratic models, some of the model parameters were calculated a priori and the rest of the model parameters were then obtained in subsequent fitti ngs. The sets of best-fit parameters obtained in this manner were more cons istent with the underlying assumptions of these models than were the sets o f parameters obtained entirely through regressions to the experimental data Thus, the extraction of parameters by fitting a model to the retention dat a of a single solute may result in unreliable values for those parameters, even in the case of a fit that would be considered good when judged by conv entional statistical criteria. That is, although parameters extracted in su ch a fashion may be suitable for optimization or similar uses, they may not be suitable for determining the appropriateness of the underlying assumpti ons of retention models. (C) 2001 Elsevier Science B.V, All rights reserved .