[R] Stress in multidimensional scaling

[Dave Roberts]

cmdscale calculates an eigenanalysis of the dissimilarity matrix, and 
does not employ "stress" per se.  Rather, it attempts to maximize 
variability along axes.

If you call the the cmdscale() function with "eig=TRUE" it returns a 
list object with the coordinates called "points" and the eigenvalues 
called "eig".  Accordingly, if you have an object returned from cmdscale 
you can look at the dimensionality of the solution with

 > x <- cmdscale(dissim.matrix,eig=TRUE)
 > barplot(x$eig)

If you really want "stress" you should use the isoMDS() function from 
MASS which performs nonmetric multi-dimensional scaling, and does 
directly employ stress.

You might also want to look at functions metaMDS in package vegan, and 
nmds in package labdsv.  There is a page at

http://ecology.msu.montana.edu/labdsv/R/lab7/lab7.html

and

http://ecology.msu.montana.edu/labdsv/R/lab8/lab8.html

that attempts to explain this.

Dave R.


Michelle DePrenger-Levin wrote:
> Hello,
> 
> We are trying to find a function to compute "stress" in our
> multidimensional scaling analysis of a dissimilarity matrix. We've used
> "dist()" to create the matrix and "cmdscale()" for the scaling. In order
> to determine the number of dimensions we would like to plot stress vs.
> dimensions. However, we cannot find a pre-made command. It seems that
> other programs may test stress as part of the algorithm as opposed to
> cmdscale() which allows us to chose the number of dimensions. Do we need
> to just code in a computation of stress? 
>  
> Thanks,
> Michelle
> 
> 
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-- 
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David W. Roberts                                     office 406-994-4548
Professor and Head                                      FAX 406-994-3190
Department of Ecology                         email droberts at montana.edu
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