Perhaps the main problem is that a principal components analysis is not intended to achieve good discrimination between groups. It is used just to get a low-dimensional overall view of any patterns of diversity. To see how well groups can be distinguished you need to compute a discriminant function (if you have just two groups) or a canonical variates analysis (for more than two groups).
As Philipp suggested, it is valid to add log centroid size as an additional variable. Adding additional information such as size might improve discrimination. However, there is also a risk. If you happen to have collected young specimens of one group and older ones from another then size might discriminate perfectly but would not work in future samples where you had specimens of similar ages. Thus size provides important additional information but it may be less useful than shape variables. -------------------- F. James Rohlf, Distinguished Professor, Graduate Program Director Dept. Ecology & Evolution, Stony Brook University, Stony Brook, NY 11794-5245 Web: http://life.bio.sunysb.edu/ee/rohlf Morphometrics: http://life.bio.sunysb.edu/morph > -----Original Message----- > From: morphmet [mailto:[EMAIL PROTECTED] > Sent: Wednesday, November 16, 2005 6:06 AM > To: morphmet > Subject: DA with PCA+CS > > One quick question: > > is it a mistake to use PCA of the shape + Centroid Size to > obtain a better discrimination in a Discriminant Analysis? > > If I use only PCA of the shape the discrimination of the > groups is not very good... > > Thanks, > Diego > -- > Replies will be sent to the list. > For more information visit http://www.morphometrics.org > > -- Replies will be sent to the list. For more information visit http://www.morphometrics.org
