[R-sig-ME] Binomial model variance and repeatability estimates with MCMCglmm

[Ned Dochtermann]

Thanks, I was aware of that for categorical and some of the other 
families but thought I could get away with it here and I wasn't quite 
sure otherwise how to calculate the relevant ratio (thanks for providing 
that too).
With smaller sample sizes repeatability still seems to get misestimated 
and stuck close to zero even with long runs but running multiple chains 
seem to resolve that.

Thanks again,
Ned

On 10/21/2014 3:05 PM, Jarrod Hadfield wrote:
> Hi,
>
> The residual variance of a binary response cannot be estimated, so use
>
> prior1 = list(R = list(V = 1, fix=1),
>               G = list(G1 = list(V = 1, nu = 0.002)))
>
> In this example it is more efficient to aggregate success/failures of 
> an individual into a multi-trial binomial response and use:
>
>  prior2 = list(R = list(V = 1, nu=0.002))
>
> sim.mcmc2<-MCMCglmm(cbind(Fail,Success)~1,
>                     family="multinomial2", prior=prior2,
>                     nitt = 260000, thin = 200, burnin = 60000,
>                     verbose=FALSE,data=ind.data)
>
> sim.mcmc2$VCV/(sim.mcmc2$VCV+pi^2/3)
>
> Cheers,
>
> Jarrod