One of the better known procedures for finding a representative composite of several different MDS solutions is based on Carroll's generalized canonical correlation model (Carroll 1968). However, the program for implementing the fitting of this model has not received wide distribution. The present paper provides a simple computational method for implementing Carroll's approach and shows its relationship to ordinary principal components analysis. In addition, we provide an algorithm for computing the parameters of Carroll's model in the presence of missing data. Each method is illustrated with data sets drawn from a marketing research study.
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