[R] Using of LME function in non-replicate data
klebyn at yahoo.com.br
Fri Mar 17 00:51:29 CET 2006
Hello all R-users!
In Jun-2005, I find the follow discussion about using
LME function ( in NLME library ) for fitting
The thread: ANOVA vs REML approach to variance
Someone expose the follow problem:
# non-replicate data
y <- c(2.2, -1.4, -0.5, -0.3, -2.1, 1.5, 1.3, -0.3,
0.5, -1.4, -0.2, 1.8)
ID <- factor( 1:12 )
varcomp(lme(y ~ 1, random = ~ 1 | ID))
# ID Within
# 1.6712661 0.2350218
Prof. Dr. Douglas Bates reply this:
> It's a spurious convergence in lme. There is no
check in lme for the
> number of observations exceeding the number of
groups. There should
> be. I'll add this to the bug reports list.
But I have one similar problem and one doubt.
I have 49 distinctive experiments split in 7 blocks (
split plot design non-replicate )
I fitting models with ~ 10 or ~ 20 coefficients (
several responses. )
it seems describe the data by
experimental versus predicted responses plot and
My doubt: The components of variance given by LME
reliable approximate estimates or this variance are
... I thinked that this varinces were calculate by
"lack of fit terms".
In the case of this variances are wrong, even so can
I use the REML coefficients estimates?
Thanks in advanced!
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