Hello everyone!
My data is composed of 277 individuals measured on 8 binary variables
(1=yes, 2=no).
I did two similar cluster analyses, one on SPSS 18.0 and one on R 2.9.2. The
objective is to have the means for each variable per retained cluster.
1) the R analysis ran as followed:
> call data
> dist=dist(data,method="euclidean")
> cluster=hclust(dist,method="ward")
> cluster
Call:
hclust(d = dist, method = "ward")
Cluster method : ward
Distance : euclidean
Number of objects: 277
> plot(cluster)
> rect.hclust(cluster, k=4, border="red")
> x=rect.hclust(cluster, k=4, border="red")
> sapply(x, function(i) colMeans(data[i,]))
> round(sapply(x, function(i) colMeans(data[i,])),2)
2) The SPSS analysis ran as follows:
Analysis --> Classify --> Hierarchical cluster analysis --> Cluster method=
Ward's method and Distance measure= Interval: Squared Euclidean distance.
After that, I computed the means of each variable for each cluster.
The problem is I have different results between the two analyses (different
clusters and means).
However, when I use the "Euclidean distance" (unsquared) in SPSS, I have the
same results!
I thought the R "euclidean" command meant the "usual square distance between
the two vectors (2 norm)" as specified in the documentation, no the
unsquared distance. Did it not?
Thanks for the comment!
Jeffrey
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