[R-sig-ME] lme() vs aov()
Federico Calboli
f.calboli at imperial.ac.uk
Thu May 22 19:16:01 CEST 2008
Hi All,
I was playing with a small dataset of 12 observations, a very basic
nested model, with 3 drugs, 2 sources for each drug and two response
counts for each source (the response is some medical parameter, of no
real interest here). The data is:
drug source response
d1 a 102
d1 a 104
d1 q 103
d1 q 104
d2 d 108
d2 d 110
d2 b 109
d2 b 108
d3 l 104
d3 l 106
d3 s 105
d3 s 107
For kicks, and because the data is balanced I thought that I could
use it to compare the results of aov() with those of lme() -- I know
the library lme4 and lmer() should be preferred, but the stuff I am
ultimately testig was done with lme.
In any case I fit 2 models and got 2 different answers:
> mod.lme = lme(response ~ drug, random = ~1|source, dat)
> mod.aov = aov(response ~ drug + Error(source), dat)
> summary(mod.aov)
Error: source
Df Sum Sq Mean Sq F value Pr(>F)
drug 2 61.167 30.583 61.167 0.003703 **
Residuals 3 1.500 0.500
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 6 9.0 1.5
> anova(mod.lme) # I use anova here to directly compare the F-test
numDF denDF F-value p-value
(Intercept) 1 6 115207.14 <.0001
drug 2 3 26.21 0.0126
(incidentally the 3 denDF here make me think the F-test is exactly
what I'd expect)
Because the results look different, I thought the possibilities are:
1) I fit 2 different models without realising it
2) one model is more conservative than the other
3) I'm completely missing some point (despite searching the archives
of R-help and R-ME)
Just to be pesky, if I check the calculations against the book I got
the data from (Zar 4th ed, pgg 304-305) they agree with the aov()
results.
Any illumination is gratefully asked for. I apologise in advance for
any annoyance past/present/future my question will cause.
Federico
--
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St. Mary's Campus
Norfolk Place, London W2 1PG
Tel +44 (0)20 75941602 Fax +44 (0)20 75943193
f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com
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