Meg: Megacluster Analytic Strategy for Multistage Hierarchical Grouping with Relocations and Replications

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Abstract
An analytic and computer strategy is introduced and demonstrated for multistage Euclidean grouping (MEG). The procedure sequentially produces first-stage clusters for independent data blocks; second-stage, higher order clusters based on a full similarity matrix for fist-stage clusters; and third-stage clusters that allow case migration to relocate prior misassignments and to optimize within-cluster homogeneity. The process is facilitated by special SAS computer codes and, in addition to conventional SAS cluster output, produces special fusion statistics, plots of all fusion statistics, and indices of homogeneity within clusters and within profile variables. The program also reports replication rates for final clusters.
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