Hi to all the people, I'm working with abundance data of some species, but containing too zero values, and the factors are the ones typical in a BACI experiment (Before-and-After-Control-Impact). Thus, these are two fixed factors. As the data does not holds the normality and homogeneity of variances assumptions of clasiccal ANOVA, I'm trying to fit a zero-altered model using the MCMC glmm library. I've two questions:
1.- how I can include an interaction between the BA (before and after) and the CI (control-impact) components in this kind of models? I'm searching in the notes available in the models but found no clear answer. My first approach to this wil be to wrote a formula like: Abundance~BA+CI+BA*CI. 2.- Even when I try to fit a model without interactions I can't do it because I obtain the following error: > fit<-MCMCglmm(Abundancia~BA+CI, random=NULL, > family="zapoisson",data=Trucha) Error in MCMCglmm(Abundancia ~ BA + CI, random = NULL, family = "zapoisson", : please use idh(trait):units or us(trait):units or trait:units for error structures involving multinomial data with more than 2 categories or zero-infalted/altered/hurdle models I don't know where is the problem, maybe because my original data is organised as (obviously with much more data): Abundance BA CI 5 1 1 3 2 1 6 1 2 Any idea or suggestion? Many thanks for your help and patience, best regards Pablo 8 2 2 -- View this message in context: http://r.789695.n4.nabble.com/MCMC-glmm-tp3304916p3304916.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.