[R-sig-ME] MCMCglmm and phylogeny - huge variance problem

[Szymek Drobniak]

Dear mixed modellers,

I'm trying to fit a comparative meta-analysis and everything's fine
but I'm getting several warnings (some of which I don't quite
understand and can't tell if they're causing the problem) and a weird
result with huge animal (ergo phylogeny-related) variance. Below is
the model and the prior, and of course the output with summary. Any
idea if this huge variance might be due to these warnings  (relating
to the tree I guess) or due to the data (which has has high variance
anyway). Could prior expansion fix these problems?

Szymek


#########(code)

prior.fil <- list(R=list(V=1,n=0.002),
G=list(G1=list(V=1,n=0.002),G2=list(V=1,n=0.002),G3=list(V=1,n=0.002)))

meta.fil <- MCMCglmm(Zr~1, random=~ref+repeat+animal, prior=prior.fil,
pedigree=tree, mev=data$mev, data=data, verbose=F,
nitt=3000000, burnin=1000000, thin=800)


###########(summary of the model)

 Iterations = 100001:4999501
 Thinning interval  = 500
 Sample size  = 9800

 DIC: 256.8579

 G-structure:  ~ref

    post.mean  l-95% CI u-95% CI eff.samp
ref   0.03544 0.0002057   0.1017     9800

               ~repeat.

        post.mean  l-95% CI u-95% CI eff.samp
repeat.   0.01121 0.0001536  0.04053     9800

               ~animal

       post.mean  l-95% CI  u-95% CI eff.samp
animal 3.765e+15 1.450e+15 4.504e+15     9507

 R-structure:  ~units

      post.mean l-95% CI u-95% CI eff.samp
units    0.2345   0.1703   0.3107     9502

 Location effects: Zr ~ 1

            post.mean  l-95% CI  u-95% CI eff.samp pMCMC
(Intercept)    -740.7 -453419.4  464404.3     9800 0.988
>

############(warnings)

Warning messages:
1: In inverseA(pedigree, nodes = nodes, scale = scale) :
  no branch lengths: compute.brlen from ape has been used
2: In `levels<-`(`*tmp*`, value = c("JJJ", "DDD", "III", "GGG", "",  :
  duplicated levels will not be allowed in factors anymore
3: In MCMCglmm(Zr ~ 1, random = ~ref + repeat. + animal, prior = prior.fil,  :
  some combinations in animal do not exist and 50 missing records have
been generated
4: In `[<-.data.frame`(`*tmp*`, dim(data)[1] -
(dim(missing.combinations)[1] -  :
  provided 50 variables to replace 2 variables
5: In `[<-.factor`(`*tmp*`, iseq, value = c("JJJ", "1", "JJJ", "1",  :
  invalid factor level, NAs generated
6: In `levels<-`(`*tmp*`, value = c("JJJ", "DDD", "III", "GGG", "",  :
  duplicated levels will not be allowed in factors anymore

-- 
Szymon Drobniak || Population Ecology Group
Institute of Environmental Sciences, Jagiellonian University
ul. Gronostajowa 7, 30-387 Kraków, POLAND
tel.: +48 12 664 52 19 fax: +48 12 664 69 12

www.eko.uj.edu.pl/drobniak