MULTIPLE CLUSTERS, TYPES, AND DIMENSIONS FROM ITERATIVE INTERCOLUMNAR CORRELATIONAL ANALYSIS
Louis L. McQuitty · Multivariate Behavioral Research · 1968
This paper extends Intercolumnar Correlational Analysis from a single, hierarchical, classification method to a multiple, hierarchical, classification method. Some advantages of the method over most other methods are: (a) it builds hierarchical classifications from the top down and thus uses all indices of every matrix or submatrix in all decisions, and (b) it provides a comprehensive base for defining the major patterns of the first hierarchical system.