MODIFICATION OF MALINOWSKI F-TEST FOR ABSTRACT FACTOR-ANALYSIS APPLIED TO THE QUAIL-ROOST-II DATA SETS

Malinowski's F-test is a popular method for selecting the number of fa ctors in abstract factor analysis. Very recently we introduced a modif ication of this F-test that is based on an alternative number of degre es of freedom. In this paper the modification is applied to the Quail Roost II data sets. These artificial data sets have recently been incl uded in a data base of reference data sets for chemometrical method te sting. Balanced scaling is applied as a preprocessing step, since the noise in the raw data violates the requirement of a constant variance. In comparison with the original test, highly improved pseudorank esti mates are obtained by using the modification. These results demonstrat e the potential usefulness of the modified F-test for the analysis of real data, since the noise structure of the Quail Roost II data sets i s, for example, very similar to the hypothesized noise structure of da ta collected from hyphenated instruments. (C) 1997 by John Wiley & Son s, Ltd.