Sorry to bother you kind folks again with my questions.  I am trying to 
learn as much as I can about all this, and I will admit that I don't 
have the proper background, but I hope that someone can at least point 
me in the correct direction.

I have created a test matrix for what I want to do:

    s1 s2 s3 s4 s5
s1 10  5  0  8  7
s2  5 10  0  0  5
s3  0  0 10  0  0
s4  8  0  0 10  0
s5  7  5  0  0 10

this is a similarity matrix (lets call it "mini") i created to run some 
tests.  thus, a self-against-self analysis gives a score of 10, and 
lower scores denote lower degrees of similarity (8 denote two items 
that are almost the same, etc).  s1 is closely related to s4 and s5, 
but slightly more closely related to s4.  s2 is related similarly at 
some medium level to s1 and s5.

i converted this into a dissimilarity matrix with R using

dissmini <- max(mini)-mini

this results in:

    s1 s2 s3 s4 s5
s1  0  5 10  2  3
s2  5  0 10 10  5
s3 10 10  0 10 10
s4  2 10 10  0 10
s5  3  5 10 10  0

if I then do

plot(cmdscale(dissmini), type="n"); text(cmdscale(dissmini), 
row.names(cmdscale(dissmini)))

I end up with a plot that shows (among other things) s2 and s5 very 
close together, closer together than s1-s5 or s1-s2 or s1-s4.   This is 
the opposite of what I would predict and what I want the plot to show.

If I instead use

plot(cmdscale(as.dist(dissmini)))

the plot is the same.

something like this:

                     s4

     s1


s5
  s2

                                                    s3

Thanks for your help,
Tom Isenbarger



--
isen@plantpath.wisc.edu
thomas a isenbarger
(608) 265-0850

	[[alternative text/enriched version deleted]]


