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

[Jarrod Hadfield]

Hi, 

There seems to be something amiss with the tree. Do you expect there to
be branch lengths? Do you get warning messages outside of MCMCglmm if
you use compute.brlen on the phylogeny?

Jarrod


On Wed, 2011-07-06 at 16:45 +0200, Szymek Drobniak wrote:
> 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
> 



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