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Retention indices for 18 monomeric stationary‐phase solvents and 33 organic solutes are factor analyzed. Six factors reproduce the data matrix near experimental error. The solvents diglycerol and zonyl E‐7 are shown to be highly unique, whereas none of the solutes behaves uniquely. Combination sets of solvent vectors and of solute vectors from the data matrix lead to models having errors within experimental error. Basic factors which might influence the solute—solvent interactions are identified by the least‐squares method of target testing. For the solvents, a number of properties, including McReynolds' constants and molecular weight, test successfully. For the solutes, carbon number and group dipole moment are representative properties which test successfully. The best combination of solvent basic factors gives errors about twice the experimental error. Combination sets composed only of McReynolds' constants do not model the data well.
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Howery et al. (1987) studied this question.
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