Fig. 2. Three distinct clusters identified across subjects.

Dendograms show results of different cluster groupings carried out on the dominant variables shown in Table 2. Variables were normalized before clustering. Subjects were assigned numbers from 1 to 20 as in Table 2 and grouped into clusters. Clustering algorithms with Euclidian distance (panel A) or correlation function (panel B) as a measure of dissimilarity yielded identical results: our sample of 20 elderly subjects had an internal structure consisting of three well-defined and stable clusters. Panel C shows result of clustering conducted only on dominant neuropsychological variables.