Message-ID: <88dd1e43-05ab-2863-223e-3abd427dab92@natur.cuni.cz>
Date: 2022-09-01T22:06:26Z
From: Martin Weiser
Subject: pattern in a few interdependent variables
Dear list members,
could You please advise me upon a not-so-multivariate problem?
We have run an experiment: we cultivated 10 plant species, each with 28
replicates, we applied two treatments (say, fertilization F and adding
the symbionts S) in a fully factorial design (F+S+, F-S+, F+S-, F-S-).
We were interested in one plant trait (T1) in response to those
treatments, but we also measured trait2 (T2) - size of the plant - as
the covariate.
We have analyzed the data in an design-based way:
T1 ~ T2 * F * S * Species (or something similar)
But, it turns out that in S+ treatments, the plants and the species
varied a lot both in T1, but also in T2 (the size) and in the level of
plant colonization by symbionts. I believe that the relation is not
unidirectional, and I would like to see how (and if) species differ in
the "symbiont colonisation-size-trait1" interplay.
One of my ideas was to take the symbiont colonisation, individual size
and trait1 as a multivariate matrix and run redundancy analysis (RDA; or
CCA) with Species identity as the canonical (constraining) variable.
Another option could be to construct the regression model II for each of
the relationships (symbionts~size, size~trait1, symbionts~trait1) and
plot the slopes for each of the species.
Do you have any other idea how to inspect the patterns?
With kind regards,
Martin Weiser
--
Please expect long response time (3d+) - this is because of family reasons