Peter Dalgaard wrote:
[snip]
Or, try looking at a smaller example where things can be worked out
explicitly: One-way ANOVA with random btw.group variation. Say 5
groups and 3 obs per group. If I got this right (please do check!),
the estimate of the between-group variance is 1/3 times the differenc
Thomas Lumley <[EMAIL PROTECTED]> writes:
> On Tue, 16 Dec 2003, Gary Allison wrote:
>
> > Hi all,
> > I didn't get a response to my post of this issue a week ago, so I've
> > tried to clarify:
> >
> > When I use lme to analyze a model of nested random effects, the variance
> > estimates of level
On Tue, 16 Dec 2003, Gary Allison wrote:
> Hi all,
> I didn't get a response to my post of this issue a week ago, so I've
> tried to clarify:
>
> When I use lme to analyze a model of nested random effects, the variance
> estimates of levels higher in the hierarchy appear to have much more
> varian
Pascal,
If every run of my simulation produced results like you saw, I would not
be concerned. But a sizable fraction of my simulation runs produce much
larger standard deviations in level 1, though level 3's estimates stay
small. I've posted the results from 500 runs at:
http://david.science
Running lme on your data set results exactly in what you expect - or do
you expect something different?
Pascal
> L1<-factor(F1f)
> L2<-factor(F2f)
> L3<-factor(F3f)
> lme(value ~ 1,random = ~ 1 | L1/L2/L3)
Linear mixed-effects model fit by REML
Data: NULL
Log-restricted-likelihood: 438.9476
F
Hi all,
I didn't get a response to my post of this issue a week ago, so I've
tried to clarify:
When I use lme to analyze a model of nested random effects, the variance
estimates of levels higher in the hierarchy appear to have much more
variance than they should.
In the example below with 4 le
