Thanks for your answers Stephen and Ben, I hope I am posting on the correct list now.
I managed so far to run the multinomial model with random effect with the following command: MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,empty) ~ habitat:trait,random=~idh(trait):mesh,family="multinomial12", data=dataA,rcov=~trait:units) (where multiple responses are different species, Habitat the explanatory variable and Mesh the random effect) The main question I am facing now is: Why the multinomial model fit does not provide by default a parameter estimate for each response category but a unique one for all of them? I had to add interactions "trait:habitat" to get the same output as a classical multinomial model... Therefore I wonder how the multinomial model is implemented in this function... any idea? The predict function is apparently not adapted for multinomial fit either and need further improvements, right? Best, Amélie -- View this message in context: http://r.789695.n4.nabble.com/Multinomial-MCMCglmm-tp4648566.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
