Folks, I'm currently at a loss. I'm developing vegetation types using
standard hierarchic clustering techniques (Euclidian distance, Ward's
method). I'm testing these groups using Multiple-Response Permutation
Procedures, which estimates the likelyhood of finding tighter clusters.
MRPP results in p-values ranging from 0.0002 to 0.90 for clusters derived
in this manner, depending on how I transform the data matrix before
My problem is that groupings which are statistically significant do not
appear to be of any ecological meaning. I'm fairly boggled by these
results, as I would assume that any sort of clustering method would always
produce groupings which are at least better than random (p < 0.50), but
this does not seem to be the case.
Any help would be appreciated. Thanks.
DIRT /\ FIRST! | Curt Seeliger
/ \ | Humbled State University
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/\____/\ | reply to cws1 at axe dot humboldt dot edu
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