[R-sig-ME] Factor level contrasts and associated fixed effect priors in MCMCglmm

[Mohammed Armani]

Deal all,
I am running a phylogenetic binary model in the package MCMCglmm (The response variable being Resp (0, 1)). One of my predictors is a categorical variable (with 3 levels: T1, T2 and T3) and I would like to set-up the model to explicitly test for differences between the levels of this factor (i.e. T1 vs T2; T1 vs T3 and T2 vs T3). I am following the GLMM worked example of https://ms.mcmaster.ca/~bolker/R/misc/foxchapter/bolker_chap.html and proceeded as follows:

contrs<-matrix(c(0,1,0,
                 -1,0,1,
                 0,-1,1),
               byrow=TRUE, ncol=3,
               dimnames=list(c("T1 vs T2",
                               " T1 vs T3 ",
                               " T2 vs T3"),
                             levels(data$T)))

sol_ctr<-solve(contrs)

newmat1<-model.matrix(~T,data=data,
                     contrasts=list(T=sol_ctr1))

datar <- with(data,data.frame(Resp,T,phylo,
                                   newmat1[,-1]))
mod_1<-MCMCglmm(Resp~ T1 vs T2+ T1 vs T3 + T2 vs T3-1,random=~phylo,family="categorical",
                 ginverse=list(phylo=inv.phylo1$Ainv),prior=prior,trunc=TRUE,
                 data=datar,nitt=3e6,burnin=3000,thin=1500)

Question:

1.       First, I would be grateful to receive some feedback if I am doing the right thing with setting the contrasts!

2.       Secondly, one of the factor levels (T2) has only success in the response variable (all=1). I understand from the MCMCglmm course note that in such instances a fixed effect prior such as B=list (mu=c (0, 3), V=diag (3)*(1+pi^2/3) can be applied. However, in the instance where an explicit contrasts is specified as I have done, I am unsure of how to specify the contrast for the fixed effect terms

Thanks.

Armani M


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