Multiple independent random effects
Michael Cone <coanil at ...> writes:
Mark, I don't think that's possible with lme4/lmer right now. Michael
It's possible, but not easy. http://rpubs.com/bbolker/varfac shows how to set up formulae/model structures that allow for different RE variances, or different residual variances, across different levels of a fixed treatment factor. Basically, you have to set up an observation-level random effect and dummy variables for each level of C other than the first, then add (0+cLevel2|obs) + (0+cLevel3|obs) + (0+cLevel4|obs) ... or equivalently you can use (0+dummy(C,"level2")|obs) + (0+dummy(C,"level3")|obs) + ... This is more elegantly doable with the flexLambda development branch ...
Am 12.09.2014 12:12 schrieb Mark Payne:
Hi, I have a mixed-effects model in lme4 like so mdl <- lmer(T ~1 + (1|A) + (1|B),...) where the factors A and B are being modelled as independent random effects. However, there is also heteroscedasticity in the problem, where the variance of T depends on a third grouping factor, lets called it C. I can fit such a model in the nlme package, using the weights=varIdent(form=~1| C) argument, but this package doesn't seem to easily support independent random effects of the form shown above... How can I get the best of both worlds here? Mark