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.