A Preliminary Study of the Effects of Within-Group Covariance Structure on Recovery in Cluster Analysis. Research Report RR-94-46.

Autor/in	Donoghue, John R.
Institution	Educational Testing Service, Princeton, NJ.
Titel	A Preliminary Study of the Effects of Within-Group Covariance Structure on Recovery in Cluster Analysis. Research Report RR-94-46.
Quelle	(1994), (55 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Algorithms; Analysis of Covariance; Cluster Analysis; Correlation; Group Membership; Monte Carlo Methods; Statistical Studies + Suchen Sie Ihr Suchwort? Algorithm; Algorithmus; Clusteranalyse; Korrelation; Gruppenzugehörigkeit; Monte-Carlo-Methode
Abstract	Monte Carlo studies investigated effects of within-group covariance structure on subgroup recovery by several widely used hierarchical clustering methods. In Study 1, subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. All clustering methods were strongly affected by within-group correlation; negative correlation yielded much poorer recovery. Smaller effects were found for the interaction of clustering method and within-group variance. Study 2 separated effects of direction of correlation from the direction of differences in the subgroup centroids. Subgroup size, within-group correlation, direction of the vector separating subgroup centroids, and distance between subgroup centroids were manipulated. Superior recovery was associated with within-group correlation that matched the direction of subgroup separative. Overall, the EML algorithm of the Statistical Analysis System yielded best recovery, followed closely by Ward's method, average linkage, and a version of the beta-flexible algorithm. Several alternative measures are discussed. Six tables and eight figures present analysis data. (Contains 52 references.) (Author/SLD)
Erfasst von	ERIC (Education Resources Information Center), Washington, DC