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