[R-sig-ME] "Animal Model" plus logistic regression

[Bertrand Servin]

Dear list,

I tried searching in the archive, but cannot seem to find a relevant
thread on my problem. I would like to fit a generalized linear
model (logit link) where the random effects are individuals and
I estimated (from genetic data) the expected correlation between
these random effects. This is sometimes called "Animal model" because
it is quite used in livestock genetics.

This could be a simple dataset:

library(lme4)

y=c(1,1,0,0)
ID=as.factor(1:4)
V=matrix(c(1,0.1,0.2,0.3,0.1,1,0,0,0.2,0,1,0,0.3,0,0,1),nrow=4,byrow=T)

The model is just logit(y) ~ mu + e

with Var(e)=V.sigma^2_a+I.sigma^2_e

So V is not to be estimated within the model fit, I just want to
get an estimate of sigma^2_a, and the model residuals.

I was thinking among these lines:

glmer(y~1|ID,family=binomial,doFit=FALSE)

and then modify something within this model.
Related question, how do I actually fit the model once
I made the modifications needed ?

Is this the right way to go ?

thanks for your help
-- 
Bertrand Servin