[R-sig-ME] multivariate mixed model for composition data : RRPP, mvabund as alternatives to permanova?

Torsten Hauffe tor@ten@h@u||e @end|ng |rom gm@||@com
Mon Apr 29 19:05:52 CEST 2019

The boral package features a straight-forward coding of nested 'random' row
effects. If I remember right, the help package includes an 2-level nested
boral uses Bayesian inferrence and not permutations and is therefore closer
to mvabund than to permanovas. Therefore, and for being not into
experimental design, I don't know whether you need a a more complicated
high-level random structure than just the 'block' and the rest go as
'fixed' effects. In that sense, boral is maybe more similar to lme4,
MCMCglmm etc than community packages like vegan.

However, the boral predictor syntax is different to the regular R formula
and does not include interactions. With model.matrix() first and then
removing the intercept, you can nevertheless specify interactions.


On Mon, 29 Apr 2019 at 18:22, Guillaume Adeux <guillaumesimon.a2 using gmail.com>

> Hi everyone,
> Does anybody have any experience with multivariate "mixed" models? And more
> specifically with the RRPP package or other alternatives to vegan::adonis
> for complex hierarchical designs?
> I took knowledge of the RRPP package (associated publication:
> https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13029 )
> but I am having a real hard time transcribing my design into actual code
> and defining against what Mean Square the different effects (including
> random) should be tested.
> The design is the following (split split split plot, very similar to oats
> dataset):
>     - 4 blocks  -> "block"
>     - each block is split into two tillage types (conventional vs.reduced)
> -> "tillage"
>     - each tillage type is split into 4 nitrogen levels   -> "N"
>     - each nitrogen level is split into 4 cover crop types  -> "CC"
> To complicate things further, 2 pseudo-replicates were carried out in the
> plots at the lowest hierarchical level (cover crops). This results in 32
> combinations of tillage, nitrogen and cover crops (128 plots total, x2 =
> 256 observations). My response is the cover per species of segetal plants.
> My objective would be to test all simple effects, first order interactions
> and the second order interaction in order to investigate things further.
> I'm really looking for something similar to vegan::adonis that takes into
> account more than one level of nesting (BiodiversityR::nested.permanova
> also only takes into account one level of nesting and does not test the
> interaction).
> Moreover, reading the Supp. Mat. of the article cited above, it is written
> that "mixed model ANOVA is possible via multimodel comparison" with
> {mvabund}. Could anyone give me more insight?
> Thank you once again for your very appreciated help,
> Guillaume ADEUX
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