envfit permutation significance

Well, just because the vector(s) in question don't hit some a priori
specified statistical significance doesn't mean the vector doesn't exist;
we can still plot it.

As for interpretation, the length of the vector is not unusual when
considered against a null distribution of r values generated by
permutation. This doesn't mean the vector is random, just that it is no
more "important" than a vector in ordination space where there was no
relationship between the axis scores and the variable for which the vector
is being tested.

You need to ask yourself whether the permutation test is valid - are you
allowed to permute the things you permuted? - and whether you have
sufficient power to detect an "effect", which usually boils down to having
enough unique permutations to get a "significant" p value.

If you want to restrict the plot to only those vectors that are
"significant", then look at the `p.max` argument in `?plot.envfit

HTH

Gavin

I have fitted a vector (a variable) using envfit to an RDA of sites,
species,
and environmental variables. The envfit permutation (999 permutations) was
not significant, but envfit placed the vector on the RDA plot. How exactly
do I interpret this plot? Is the placement of the vector meaningless (just
random) because the permutation result was not significant? or does the
vector placement have meaning, but it just cannot be predicted from the RDA
with confidence?



--
View this message in context:
http://r-sig-ecology.471788.n2.nabble.com/envfit-permutation-significance-tp7579206.html
Sent from the r-sig-ecology mailing list archive at Nabble.com.

_______________________________________________
R-sig-ecology mailing list
R-sig-ecology at r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology

Gavin Simpson, PhD

	[[alternative HTML version deleted]]