I'm conducting an hierarchical cluster analysis of binary variables in SPSS (Complete-linkage clustering with Sokal and Sneath 1 as the distance measure). For guidance on the number of clusters to use, I'm using the Ratkowsky-Lance index, which is recommended for binary variables. (I'm using the macros that @ttnphns has awesomely published.)
However, the index is always higher for higher numbers of clusters. I've tested 2 to 20 clusters and the index just increases with each additional cluster. I thought one should simply choose the highest index, but that can't be the case, right? Am I rather supposed to interpret the plot more like a scree plot, looking for the elbow / inflexion point?