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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.