# Mahalanobis distance in a hierarchical cluster analysis in SPSS

I am conducting a hierarchical cluster analysis in SPSS on my database with several neuropsychological and psychiatric variables. In my database, some of my variables (that is, two pairs of variables) have correlations $r > .80$. My first thought was to eliminate these variables from my cluster analysis. However, another option is to use Mahalanobis distance as the distance measure, because this measure takes the correlation in account (according to, e.g., Multivariate Data Analysis by Hair et al.).

My question is, if there is a way as to perform the hierarchical cluster analysis in SPSS using the Mahalanobis distance? I am not familiar with R or SAS, so my preference would be a method using SPSS.

• There is no much use of Mahalanobis distance in cluster analysis, typically, because covarince matrices can be different for different clusters, and you don't know clusters in advance. If your variables strongly correlate but your clustering method "prefers" uncorrelated features, do PCA first to ortogonalize them. If you still think you need a SPSS function to compute a matrix of Mahalanobis distance between cases (pairwisely) - I have written one. (Unfortunately, my web-site is currently offline, so you can't take it, then leave me your email and I'll send.) – ttnphns Aug 18 '14 at 14:00