[R-sig-ME] code for multiple membership models?
j.hadfield at ed.ac.uk
Sun Aug 14 11:59:34 CEST 2011
If I understand correctly I think you can just add the level-1 and
level-2 covariates into the fixed effects and they will be taken care
of appropriately. With 150K observations MCMCglmm may be too slow but
that depends on the complexity of the model. The presence of some
level 1 units across all levels of the level-2 units suggests that
the mixed model equations may be quite dense and slow to solve, but
you would have to try it out. The implementation of multimembership
models in MCMCglmm is not yet ideal because the design matrix for the
multimembership part is initially dense and then coerced into sparse.
This means that setting up the model prior to MCMC can be costly in
time/memory. I have plans to change this.
On 5 Aug 2011, at 03:06, Andrei Boutyline wrote:
> Dear all (and especially Doug, Jarrod and Malcolm),
> About a month ago, there was a really useful discussion between
> Doug, Jarrod
> and Malcolm about fitting multiple membership models (
> 2011q2/006320.html). I
> was hoping that some of you could kindly offer some follow-up advice.
> I am trying to implement something very similar to what was
> recommended in
> that thread, but with the addition of covariates on both levels. It's
> pretty clear to me how to add covariates on level 1, but I do not
> understand how to add covariates on level 2. Could you please
> explain how
> to do this?
> Also, I have roughly 120 level-2 units, and 150,000 level-1 ones.
> Some of
> those level-1 units are members of almost all 120 level-2 units.
> Should I
> be worrying that the resulting model will be too large to estimate in
> reasonable time (e.g., a day or two), or can these solutions handle
> Thank you very much,
> Andrei Boutyline
> University of California, Berkeley
> PhD Student, Sociology
> www.ocf.berkeley.edu/~andrei <http://www.ocf.berkeley.edu/%7Eandrei>
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