Dear ME users,

Apologies if this is a naive question, I am new to using MCMC glmm. I have been working through the tutorial, using some of my own data, and I thought I had followed the steps correctly. The model I have been fitting is:

AMstem3<-MCMCglmm(log(stem)~Dist_fr_A,random=~Block+animal,pedigree=Ped,data=SapRO,prior=prior1.3,
family="gaussian")
Briefly, I want to see how the Distance variable (continuous) affects stem weight, which I have log transformed as the raw data is heteroscedastic. Block is field block, and I am fitting the animal random effect to take into account different relatedness between individuals (I'm not at the moment trying to estimate Va).

When I tried this model last night, I could get the 95% CIs using this function
HPDinterval(AMstem3$Sol[,"Dist_fr_A"])
HPDinterval(AMstem3$VCV)

When I tried this morning, I get the following error message
Error in function (classes, fdef, mtable)  :
  unable to find an inherited method for function "HPDinterval", for signature "mcmc"
Can anyone explain what  has gone wrong? I've tried changing the terms in the model, but that doesn't help, so I think I must have changed something in R elsewhere? Or else missing something completely obvious.

Question 2: I dont think MCMCglmm is actually logging my stem variable because the fixed effect parameter estimate from the model above (AMstem3) are about a factor of 10 out from the fixed effect estimate from
a similar model, fit in lme4, without the animal effect and very similar to the same model using the raw stem weight (see below). Do I need to specify the log transform differently?

AMstem3c Dist_fr_A  posterior mode: -0.004236659
versus:
stem5a<-lme(log(stem)~Dist_fr_A,random=~1|Block,data=SapRO,na.action=na.omit)
Fixed effect Estimate: Dist_fr_A   -0.0004442 (SE=0.00006136)
and:
stem5b<-lme(stem~Dist_fr_A,random=~1|Block,data=SapRO,na.action=na.omit)
Fixed effect Estimate: Dist_fr_A   -0.004342 (SE=0.0006714)

Thank you very much for your help,

Rebecca Ross
DPhil Candidate,
University of Oxford.




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