[R] LMMs with some variance terms forced constant

[Ben Bolker]

Erica E.M. Moodie, Dr. <erica.moodie <at> mcgill.ca> writes:

> I have been asked to help perform a meta-analysis with individual-
> and aggregate-level data. I found a nice article on this, and the
> idea is easy to understand: use a mixed effects models, but for the
> studies where there is only aggregate level data, force the variance
> to be that which was observed. Unfortunately, I am struggling to see
> how to implement this in R. I am familiar with "standard" mixed
> model formulations using nlme and lmer, but not able to see how to
> force this specific variance structure on my model so that some
> variance terms are not estimated.

  No solutions, but a few ideas:

 * I assume this is beyond the capacities/flexibility of the metafor package?

 * It's possible that the regress package
 http://cran.r-project.org/web/packages/regress/index.html
could be made to do this

 * There *may* be a way to do this with the pdStruct structures in nlme
(read the relevant bits of Pinheiro and Bates 2000, then stare at
your computer really hard for a while and see if anything comes to you),
although I suspect not

 * you can 'roll your own' mixed models in a flexible way with
WinBUGS/JAGS, maybe now Stan (if you want to be an early adopter!),
all of which have good R interfaces; it's conceivable that AS-REML
can do this too
 
 * follow-ups to r-sig-mixed-models please