[R-sig-eco] mixed effects in ordination (?)

[Bob O'Hara]

This doesn't sound like an ordination problem: it's more similar to a 
standard mixed model regression. There are several ways to approach 
this, for example Ben Bolker has some (old) notes here:
<https://rpubs.com/bbolker/3336>

I'd suggest you start by running the analyses on each trait 
individually, as that way you can make sure you have the model sorted 
correctly. The step up to the multivariate model just needs some work 
understanding what the relevant R package wants.

HTH

Bob

On 12/01/17 14:12, Martin Weiser wrote:
> Dear friends,
>
> Could you please help me with analysis? I am afraid that it involves
> crossed random effects in the mixed-effect constrained ordination
> setting, so to say.
>
> Goal:
> Show an effect of the species trait (single one) and treatment (four
> levels, quantitative scale) on parameters. Trait x treatment
> interaction is possible. If possible, show changes through time.
>
> Data:
> Individuals of 7 species, subjected to 4 treatment levels (fully
> factorial) - from 6 to 12 individuals in each combination. Each
> individual scored 4 times (same times: 1st wk, 2nd wk, 3rd wk, 4th wk).
> Several (10) parameters scored every time on each individual.
>
> What I did:
> In order to avoid multiple testing (the parameters are likely to be
> correlated to each other), I decided to use multivariate analysis
> (RDA). I am by far much more accustomed to vegan than ade4, so excuse
> me if I use some "veganisms". Predictors: time, trait, treatment
> (possibly with interactions), conditioned on individual identity to
> avoid treating records from the same plant as independent. Variance
> partitioning.
>
> Here comes the problem: how to set permutations in order to be able to
> report p_vals (some people just are not happy without them)? Since
> individuals of the same species share the same trait value, maybe the
> right way is to: shift observations within individual (if time is among
> predictors for the particular model) and permute trait value among
> species. Is it so? Is this treatment of the pseudoreplication at the
> species level (i.e. only in the significance testing, not in the
> ordination per se) ok?
>
> I also tried to use different approach: I averaged all params
> individual-wise (getting rid of temporal pseudoreplication, but also
> time effects), and subsequently I averaged the result within treatment
> x species levels. I assume that I can go for simple free permutations
> this way? Pity is that this way, I cannot see development in time.
>
> And another way: I averaged params for species x treatment x time
> groups, ignoring interdependence of records from the same individual,
> hoping that the effect of an individual "dissolves" in the average. Is
> that meaningful? If yes, what is the appropriate permutation structure
> in this case?
>
> But maybe I miss something and there are better ways how to deal with
> this problem?
>
> Any suggestions (ok: not any, just those made in an attempt to help :-)
> ) are appreciated.
>
> With the best regards,
> Martin Weiser
>
> _______________________________________________
> R-sig-ecology mailing list
> R-sig-ecology at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>


-- 
Bob O'Hara

NEW EMAIL: bob.ohara at ntnu.no
NOTE NEW ADDRESS!!!
Institutt for matematiske fag
NTNU
7491 Trondheim
Norway

Mobile: +49 1515 888 5440
Journal of Negative Results - EEB: www.jnr-eeb.org