I want to fit a random effects model with two separate nested random
effects. I can easily do this using the `lmer` package in R. Here's how:
model<-lmer(y ~ 1 + x + (1 | oid/gid) + (1 | did/gid), data=data)
Here, I'm fitting a random intercept for `oid` nested within `gid` and
`did` nested within `gid`. This works well. However, I want to fit a model
where the variance of the intercept changes with the `gid` for both the
random effects. `nlme` package is capable of doing that. However, it's not
clear how. The best I could do is like so:
model <- lme(y ~ 1 + x, random=list(gid=~1, oid=~1, did=~1),
weights=varIdent(form=~1|gid), data = data)
but this nests the `did` within `oid` and `gid` nested together. I tried to
use the idea from a similar [question][1], which seems like a close problem
but the answer has not been explained well in that question. I hope someone
can figure this out.
[1]:
https://stats.stackexchange.com/questions/58669/specifying-multiple-separate-random-effects-in-lme
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