[R-sig-ME] Mixed-model-binary logistic model with dependence between individual repeated measures

Gavin Simpson gavin.simpson at ucl.ac.uk
Fri Jan 7 19:08:51 CET 2011

On Fri, 2011-01-07 at 11:49 -0500, Ben Bolker wrote:
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<snip />
>  I do not
> > want to assume that. In addition I would like to be able to chose
> > other distributions than the normal for my random effect, which is
> > not possible in SAS (proc NLMIXED). 
>   It's not possible in R either as far as I know.

I was reading the article in the latest issue of the R Journal on the
hglm package, and although I was only giving it a cursory scan over
lunch it looks like it might be able to fit the sort of model implied
here; random effects distributed as a member of the exponential family.


> The generalized estimating
> > equation packages are probably not an option as I do not whant
> > marginal models. I will look at the references you suggested. Thank
> > you. /Anna
> > 
>   If you want a non-marginal model with non-normal random effects and
> within-individual correlation structures other than compound symmetry
> (i.e. simple block structures), you are probably going to have to
> construct your own solution with WinBUGS or AD Model Builder or ... ? If
> you're lucky, MCMCglmm may be able to do what you want -- I would check
> it out. (Molenbergh and Verbeke's book on longitudinal models describes
> approaches for non-normal random effects, but in the context of LMMs
> (i.e. normally distributed errors) -- they may have done something to
> extend this stuff to GLMMs more recently.  It's possible that someone
> out there has done what you want and encapsulated it into a canned
> package, but I doubt it.
>    cheers
>     Ben Bolker
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