[19275] in s-news-athena
[S] What is residual error in a saturated model fit with lme?
daemon@ATHENA.MIT.EDU (Francis_Bruey@cytec.com)
Tue Sep 21 09:33:33 1999
From: Francis_Bruey@cytec.com
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Date: Tue, 21 Sep 1999 09:21:59 -0400
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All:
Consider the following experiment:
Factor A with 8 levels applied to 24 experimental units (3 per
level) in completely randomized fashion.
Each unit is measured at 4 stages (initially and then after each of
3 consecutive applications of a standardized stress).
Dataframe has 96 rows, with columns Y (numeric response), uniq.unit
(factor, unique unit identifier), A (factor), and stage (factor).
Fit with aov() using model:
aov(Y ~ (A/uniq.unit)*stage)
has zero residual error.
Fit with lme() using model:
lme(fixed = Y ~ A*stage, ran = ~ stage | uniq.unit)
has nonzero residual error. Is this model not saturated (am I
misunderstanding lme syntax)? If it is saturated, what is the
residual error estimating?
Using S-Plus 2000 on PC with Win95.
Thanks,
Francis Bruey
Francis_Bruey@st.cytec.com
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