Skinner (1979) has described a generalized principal components model for classification research that assumes interval or quasi-interval data. First, a parsimonious set of typal dimensions is sought through a multiple replication design, and then relatively homogeneous subgroups are identified within this low dimensional space. The purpose of this paper is to describe preliminary transformations whereby the model may be extended to situations where the data are of either categorical or rank-order metric.
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