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 > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-phylo mailing list - Rfirstname.lastname@example.org > https://stat.ethz.ch/mailman/listinfo/r-sig-phylo > Searchable archive at > http://email@example.com/ > > > [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list - Rfirstname.lastname@example.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://email@example.com/