----- Original Message -----
Sent: Friday, May 30, 2003 2:47 PM
Subject: RE: [S] mixed models
There are many useful
functions you may apply to a fitted lme object:
summary(
)
fitted(
)
resid(
)
predict( )
intervals(
)
update(
)
coef(
)
fixef(
)
ranef(
)
For the intervals( )
function, you can use which = "var-cov" to extract
the confidence
intervals for the random effects and within-group fixed
effects variance
components.
Also, for multilevel
random effects models, you can use the level =
option in (for
example) ranef( ). This allows you to extract the
random
effects at various
levels. The same comment applies to the fixed
effects
which may be extracted
using fixef( ).
You might want to
invest in the excellent book "Mixed Effects Models
in S and Splus" by
Jose Pinheiro and Douglas Bates. It is well worth
the
money and will save
you a lot of grief. Someone on the R listserv once
said (I don't remember
who) that mixed models in R/Splus are a "space
shuttle, not a bottle
rocket." That's certainly true. There are lots of
useful
applications for these
models, but they are extremely sophisticated and
require a
correspondent amount of training.
Best,
david
paul
Hello,
After using m1<-lme(....) I can get linear
predictors by predict(m1,newdata=new).. However the results is a vector
of predicted valued only.. there no options to get confidence limit.. Is
there a way of getting confidence limits for linear predicted
values from an lme object?
Thanks
Osman