Rotations for PCoA?
On Mon, Oct 19, 2009 at 10:12 AM, Jan Hanspach <jan.hanspach at ufz.de> wrote:
Dear Sarah, that sounds good to me, thanks! Still, I have two more questions: The variable fitting with vf() does only work when I "dummy-transform" my categorical variables. Are the derived correlations then still comparable to the Gower distance - PCoA scores where my categorical variables where defined as such?
I think it only makes sense with quantitative variables. There's no "direction" to categorical variables, so how could you fit one? Usually with categorical variables I plot the ordination with different symbols to denote the class of the categorical variables, and look at pattern that way.
Is it reasonable to do more than the correlations with two axes with vf(), i.e. after calculating the correlation for the first and the second axis doing the same for the third and the forth? I guess this is a very naive question, but shouldn't this work for the p-Values since they are calculated with a permutation procedure?
You're fitting the variables to that ordination diagram. It's entirely possible that the best fit for dimensions 3 and 4 of a four-dimensional fit are not the same as the best fit of axis 3 and 4 by themselves. So it depends on your question. Alternatively, I think the vegan package has a more sophisticated vector- fitting function. Sarah
Sarah Goslee http://www.functionaldiversity.org