In statistics, especially in biostatistics, cophenetic correlation (more precisely, the cophenetic correlation coefficient) is a measure of how faithfully a  dendrogram preserves the pairwise distances between the original unmodeled data points. Although it has been most widely applied in the field of         biostatistics (typically to assess cluster-based models of DNA sequences, or other taxonomic models), it can also be used in other fields of inquiry        where raw data tend to occur in clumps, or clusters. This coefficient has also been proposed for use as a test for nested clusters.

[此贴子已经被作者于2008-7-19 2:03:01编辑过]

It is procedure built into NCSS which used to help find best cluster solution. As NCSS said: Cophenetic Correlation is the Pearson correlation between the actual distances and the predicted distances based on this particular hierarchical configuration. A value of 0.75 or above needs to be achieved in order for the clustering to be considered useful."