Correlation between qualitatively distributed predicting variables and chemical terms in acridine derivatives using principal component analysis

When biological variables are not continuously distributed, the multiple and multivariate regression analysis cannot be used to correlate these variables against chemical regressors. As the employment of discriminant analysis requires the homogeneity of dispersion matrices and, that n hp where n h = degree of freedom of hypothesis, p =number of chemical terms, the reliability and validity of this method is highly questionable here. An alternative method is based on the principal component analysis where multicategory variables of drug responses can be classified into measures of inactive, slightly active, sufficiently active, and highly active drugs, for instance. The rules for classification are based on biological sources that can be expressed by chemical terms, too. An example adapted from antitumor action of acridine derivatives shows the working technique.