I'm working with capscale and permutest for the first time, and having
trouble getting statistical analyses for more than one constraining
variable. I've read the documentation, but setting first=FALSE or using
by="axis" doesn't seem to be helping. capscale seems to be fine, I receive
output for more than one constrained axis. What am I doing wrong?

capscale.Nrem.results<-capscale(as.dist(qiime.data$distmat)~
N+rem+N*rem+Condition(dateFac), factor.frame)
capscale.Nrem.results


                Inertia Proportion Rank
Total          1.454538
Real Total     1.459802   1.000000
Conditional    0.117117   0.080228    1
Constrained    0.386228   0.264576    3
Unconstrained  0.956457   0.655197   22
Imaginary     -0.005264               2
Inertia is squared Unknown distance

Eigenvalues for constrained axes:
   CAP1    CAP2    CAP3
0.29869 0.05395 0.03359

Eigenvalues for unconstrained axes:
   MDS1    MDS2    MDS3    MDS4    MDS5    MDS6    MDS7    MDS8
0.27719 0.13725 0.11048 0.06691 0.05551 0.04940 0.03892 0.03468
(Showed only 8 of all 22 unconstrained eigenvalues)


sig.Nrem <- permutest(capscale.Nrem.results,permutations=999, by="margin",
model="direct",first=FALSE)
sig.Nrem

Permutation test for capscale

Call: capscale(formula = as.dist(qiime.data$distmat) ~ N + rem +
Condition(dateFac) + N:rem, data =
factor.frame)
Permutation test for all constrained eigenvalues
Pseudo-F: 2.961281 (with 3, 22 Degrees of Freedom)
Significance: 0.001
Based on 999 permutations under direct model.

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