Dear all, I would like to add mixed effects in a multinomial model and I am trying to use MCMCglmm for that.
The main problem I face: my data set is a trapping data set, where the observation at each trap (1 or 0 for several species) have been aggregated per trapline (i.e. 25 traps). Therefore we have a proportion of presence/absence for each species per trapline. ex: ID_line mesh habitat Apsy Mygl Crle Crru Miag Miar Mimi Mumu Misu Soar Somi 11 028S6A 28 copse 2 0 0 0 0 0 0 0 0 0 0 12 028S6B 28 copse 1 1 0 0 0 0 0 0 0 0 0 13 028S6C 28 hedge 2 0 0 4 0 0 0 0 0 0 0 14 028S6D 28 hedge 1 0 0 7 0 0 0 0 1 0 0 15 028S6E 28 hedge 7 0 0 1 0 0 0 0 0 0 0 empty 11 28 12 28 13 24 14 21 15 22 When I run the following: > test1 <- MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,Miar,Mimi,Mumu,Misu,Soar,Somi,empty)~habitat,random=~mesh,family="multinomial12",data=metalSmA[,c(2,9,23:34)],rcov=~us(trait):units) I got some error concerning the variance structure: > "ill-conditioned G/R structure: use proper priors if you haven't or rescale data if you have" I guess that the problem comes from the nature of my observations which are frequencies instead of 0/1 per unit Does someone know if a multinomial model fitted with MCMCglmm can handle those frequencies table and how to specify the good G/R variance structures? Regards Amélie Vaniscotte ______________________________________________ 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.
