[R] Examining how cases are similar by cluster, in cluster analysis

[Bob Green]

Hello,

I used the following code to perform a cluster analysis on a 
dataframe consisting of 12 variables (coded as 1,0) and 63 cases.



FS1 <- read.csv("D://Arsontest2.csv",header=T,row.names=1)

str(FS1)

dmat <- dist(FS1,  method="binary")

cl.test <- hclust (dist(FS1, method ="binary"), "ave")

plot(cl.test, hang = -1)



Each case has an id and the dendogram identifies the respective cases 
which constitute each cluster. What I am seeking advice on is how to 
examine the variables on which the cases are similar, within each cluster.



sort (hcli8 <- cutree(cl.test, k=8)) identifies that the following 
cluster 2is comprised of the following cases:

1641 2295 2594 2654 2799 3213 3510  3513 2958 3294

    2         2        2       2        2        2        2        2 
       2        2



This code provides means for the variables by cluster. In relation to 
cluster 2 it appears the cases should have no clear motive and be depressed :

round(sapply(x, function(i) colMeans(FS1[i,])),2)

                               [,1]   [,2]   [,3] [ ,4]  [,5] [,6] [,7] [,8]

depressed        0.00 0.33 0.00  0.0    0  0.6 0.00 0.08

unclear             0.33 1.00 1.00  1.0    0  0.0 0.07 0.12



I can manually, examine this variable by variable and look at how 
each of the cases in cluster 2 are similar on the variables. I am 
looking at a more efficient and quicker way to do this.

Bob