Dear list

I'd very much like to calculate some HPD intervals for the fixed parameters in a lmer model containing crossed and correlated random effects. However, I have not been able to find a solution for this type of model after a pretty thorough search of discussion threats or worked examples. Is this possible at the moment with lme4 (function or work around), or do I have to change packages and try something like mcmcglmm?

My data contains 1917 growth measurements (Increment) from 704 fish (FishID) and the data is sampled from 29 years (Year). I'm interested in the effects of age (2-18 years) and water temperature (temp) on growth. My model is:

M1<-lmer(log(Increment)~log(Age)+temp+(log(Age)|FishID)+(1|Year),data,REML=T)

HPDinterval requires an mcmc object, but when I try
mcmcsamp(M1, n=1000)

I receive the following error:
Error in .local(object, n, verbose, ...) :
  Code for non-trivial theta_T not yet written
I understand this is because MCMCsamp doesn't yet cope with correlated random effects? On the glmm wikidot page there is code to generate confidence and prediction intervals on predictions- could I use some of this to get a what I'm after (if so, which bits)? I haven't used mcmcglmm before, so ideally would like to stay with the more familiar lme4 if possible to expedite the analyses!

Any thoughts/ suggestions are much appreciated.

John


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