[R] bVar slot of lmer objects and standard errors
Spencer Graves
spencer.graves at pdf.com
Thu Dec 29 12:57:47 CET 2005
Have you received a satisfactory reply to this post? I haven't seen
one. Unfortunately, I can't give a definitive answer, but I can offer
an intelligent guess. With luck, this might encourage someone who knows
more than I do to reply. If not, I hope these comments help you clarify
the issue further, e.g., by reading the source or other references.
I'm not not sure, but I believe that
lmertest1 at bVar$schoolid[,,i] is the upper triangular part of the
covariance matrix of the random effects for the i-th level of schoolid.
The lower triangle appears as 0, though the code (I believe) iterprets
it as equal to the upper triangle. More precisely, I suspect it is
created from something that is stored in a more compact form, i.e.,
keeping only a single copy of the off-diagonal elements of symmetric
matrices. I don't seem to have access to your "nlmframe", so I can't
comment further on those specifics. You might be able to clarify this
by reading the source code. I've been sitting on this reply for several
days without finding time to do more with it, so I think I should just
offer what I suspect.
The specifics of your question suggest to me that you want to produce
something similar to Figure 1.12 in Pinheiro and Bates (2000)
Mixed-Effects Models in S and S-Plus (Springer). That was produced from
an "lmList" object, not an "lme" object, so we won't expect to get their
exact answers. Instead, we would hope to get tighter answers available
from pooling information using "lme"; the function "lmList" consideres
each subject separately with no pooling. With luck, the answers should
be close.
I started by making a local copy of the data:
library(nlme)
OrthoFem <- Orthodont[Orthodont$Sex=="Female",]
Next, I believe to switch to "lme4", we need to quit R
completely and restart. I did that. Then with the following sequence
of commands I produced something that looked roughly similar to the
confidence intervals produced with Figure 1.12:
library(lme4)
fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem)
fm1.s <- coef(fm1OrthF.)$Subject
fm1.s.var <- fm1OrthF. at bVar$Subject
fm1.s0.s <- sqrt(fm1.s.var[1,1,])
fm1.s0.a <- sqrt(fm1.s.var[2,2,])
fm1.s[,1]+outer(fm1.s0.s, c(-2,0,2))
fm1.s[,2]+outer(fm1.s0.a, c(-2,0,2))
hope this helps.
Viel Glueck.
spencer graves
Ulrich Keller wrote:
> Hello,
>
> I am looking for a way to obtain standard errors for emprirical Bayes
estimates of a model fitted with lmer (like the ones plotted on page 14
of the document available at
http://www.eric.ed.gov/ERICDocs/data/ericdocs2/content_storage_01/0000000b/80/2b/b3/94.pdf).
Harold Doran mentioned
(http://tolstoy.newcastle.edu.au/~rking/R/help/05/08/10638.html)
that the posterior modes' variances can be found in the bVar slot of lmer
objects. However, when I fit e.g. this model:
>
> lmertest1<-lmer(mathtot~1+(m_escs_c|schoolid),hlmframe)
>
> then lmertest1 at bVar$schoolid is a three-dimensional array with dimensions (2,2,28).
The factor schoolid has 28 levels, and there are random effects for the
intercept and m_escs_c, but what does the third dimension correspond to?
In other words, what are the contents of bVar, and how can I use them to
get standard errors?
>
> Thanks in advance for your answers and Merry Christmas,
>
> Uli Keller
>
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--
Spencer Graves, PhD
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