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Download full textFinch, Holmes; Huynh, Huynh – 2000
One set of approaches to the problem of clustering with dichotomous data in cluster analysis (CA) was studied. The techniques developed for clustering with binary data involve calculating distances between observations based on the variables and then applying one of the standard CA algorithms to these distances. One of the groups of distances that…
Descriptors: Algorithms, Cluster Analysis, Monte Carlo Methods, Responses
Donoghue, John R. – 1995
A Monte Carlo study compared the usefulness of six variable weighting methods for cluster analysis. Data were 100 bivariate observations from 2 subgroups, generated according to a finite normal mixture model. Subgroup size, within-group correlation, within-group variance, and distance between subgroup centroids were manipulated. Of the clustering…
Descriptors: Algorithms, Cluster Analysis, Comparative Analysis, Correlation
Donoghue, John R. – 1994
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…
Descriptors: Algorithms, Analysis of Covariance, Cluster Analysis, Correlation
