... as regarding the "recognition" of groups in a
continuum without prior group assignment, one method
not mentioned so far is mixture modelling, which is
simply attempting to fit the data to a mixture of
e.g. gaussians. Criteriae such as the Akaike Information
Criterion may be used to get some idea about a "reasonable"
number of groups, although a proper significance test
is not really available.

And then you have all those old clustering methods,
including more or less desperate attempts to calculate
some kind of significance (beware).

If the points are assigned to groups from independent
information, there are the standard statistical tests.
Since you are primarily interested in PC1, a one-way
ANOVA might be sufficient, although I think a MANOVA on
all PCs would be better.

All these methods are available in e.g. R or PAST.



Oyvind Hammer
Natural History Museum
University of Oslo



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