[R-sig-ME] lmer: problem in crossed random effect model with very different variances

[Michael Li]

Hi, I  remember seeing this mentioned somewhere but couldn't find it.

I used lmer to fit a simple linear mixed model with two crossed random
effects, day and analyst, with no other fixed effects.  So the syntax
is something like:

lmer (y ~ (1 | day) + (1 | analyst), data = data)

I can also fit the same model in PROC MIXED. Most of the time I got
the same answers.  But there seems to be a problem with lmer when one
of the random effect has a much smaller variance than others.

In my case, SAS would give random effect variances of 1552, 599133 and
213814 for analyst, day and residual effects, respectively but lmer
gives 2x10^-12, 599050, and 214680.  Basically all parameter estimates
are the same (more or less), except that lmer gives very tiny estimate
for the random effect of 'analyst'.

I probably should have used log-transformed y.  But aside from that,
how can I get lmer to give a sensible answer?  Or is SAS giving the
right answer?

Thanks,

Michael