Dear collegues,
Sender: [EMAIL PROTECTED]
Precedence: bulk
Reply-To: [EMAIL PROTECTED]


About the above discussion on the linear measurements data for multivariate 
analysis, I should state that most times my problem (and I expect the problem 
of many people that wrks with it) is not of rows/columns number (that most 
times is ok, at leats in the cases I saw) nether of multivariate normality (I 
use R-project program, which as a test of multivariate normality, so it is easy 
to test) or lack of homogeneity of variances (this is a bit more dodgy, but the 
ref. I saw state that if you test unniveriate variances homogeneity (e.g. 
Bartlett test) it shoud give a good indication of the data variances). 
The problem that (I supose) most biologists encounter are the collinearity 
between variables... which strongly influences the representation givn by the 
PCA. I think this also happens in the NMDS, discriminant and canonical analysis.

I probably did not made myself clear in the email. I am sorry...
For me, it is very interesting that this things are debate in the list, and 
different people shows different solutions and bibliography, it is realy nice.

In relation to the article from Biometrika, does anyone have the pdf? We dont 
have the journal in this college.
In relation to the robustmess of the techniques to lack of normality, I agree 
with our colegue (so... I share your feelings of daring to state it... 
jijijij ;-))

thank you for all,
Cheers,
Marta


-------------------------------------------------
This mail sent through IMP: http://horde.org/imp/



==
Replies will be sent to list.
For more information see http://life.bio.sunysb.edu/morph/morphmet.html.

Reply via email to