Remaining within-cluster heterogeneity: a meta-analysis of the "dark side" of clustering methods

In a meta-analysis of articles employing clustering methods, we find that little attention is to remaining within-cluster heterogeneity and that average values are relatively high. suggest addressing this potentially problematic "dark side" of cluster analysis by two coefficients as standard information in any cluster analysis findings: a -of-fit measure and a measure which relates explained variation of analysed data to explained variation of simulated random data. The second coefficient is to as the Index of Clustering Appropriateness (ICA). Finally, we develop a scheme depicting acceptable levels of remaining within-cluster heterogeneity. (authors' abstract)