[R] glmmPQL and additive random effects?

[Steve Buyske]

I'm a bit puzzled by how to write out additive random effects in 
glmmPQL. In my situation, I have a factorial design on two 
(categorical) random factors, A and B. At each combination, I have a 
binary response, y, and two binary fixed covariates, C and D.

If everything were fixed, I would use
	glm(y ~ A + B + C + D, family = binomial)

My first thought was to use
	glmmPQL(y ~ A + B, random = ~ C + D, family = binomial)
but glmmPQL wants to see a grouping variable in the random term. Something like
	glmmPQL(y ~ A + B, random = ~ C + D | CD, family = binomial)
where CD is a a variable combining C and D, eats up all my memory, while
	glmmPQL(y ~ A + B, random = ~ 1 | CD, family = binomial)
doesn't seem like the model I want.

Perhaps this model is too hard to fit, but before I quit this 
approach I want to make sure that I'm not just coding it incorrectly.

Thanks,
Steve Buyske