Factor analysis has been traditionally utilized for three broad purposes: First, as a data reduction technique which will hopefully simplify a multivariate situation to a smaller set of dimensions and enable the researcher to utilize data on a large number of variables; second, as an indexing device in which overtly manifested data are transformed to provide the latent or unobservable trait of a phenomenon; finally, as a cluster technique which helps the researcher to classify a variety of observations into a small set of clusters which are also generally ordered. All three approaches have used a common starting point, namely, a matrix of correlations either among the variables (Rtype factor analysis) or among the observations (Qtype factor analysis). In other words, factor analysis has been limited to associative relations.