Hi everybody,

Many thanks for all your inputs. After some digging, I think that MCMCglmm
is a good way to go. However, I am an illiterate in Bayesian modelling and
will probably have to seek for advice elsewhere, like r-sig-mixed-model.

Cheers,
Nicolay

On Wed, Aug 1, 2018 at 10:28 AM Masahito Tsuboi <masahito.tsu...@ibv.uio.no>
wrote:

> Hi list,
>
> I second Jon's suggestion for using phylogenetic mixed model. This seems
> to be the closest to what Nicolay is after.
>
> Yet another option is "SLOUCH" package in R, which can handle
> within-species variation while performing phylogenetic corrections. Here
> are some example codes.
>
> *https://kopperud.github.io/slouch/articles/introduction.html
> <https://kopperud.github.io/slouch/articles/introduction.html>*
>
> Hope you will find a suitable solution from one of those.
>
> Best,
> Masahito
>
> On 1 Aug 2018, at 14:37, jonnations <jonnati...@gmail.com> wrote:
>
> You will want to try Bayesian mixed modeling which can handle your species
> # problem by using “species” as a group level (i.e. “random”) effect. I
> would recommend r packages brms and MCMCglmm and their vignettes. Both have
> detailed “phylo” examples.
>
> Maybe check out the r-sig-mixed-model listserv as well. Lots of similar
> questions and good advice show up on there.
>
> Good luck!
> Jon
> --
> Jonathan A. Nations
> PhD Candidate
> Esselstyn Lab <http://www.museum.lsu.edu/esselstyn>
> Museum of Natural Sciences <http://sites01.lsu.edu/wp/mns>
> Louisiana State University
>
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>
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