[R] Basic LME
Peter Dalgaard BSA
p.dalgaard at biostat.ku.dk
Tue Apr 8 19:08:41 CEST 2003
<ritz at dina.kvl.dk> writes:
> Martin Hoyle <plxmh at nottingham.ac.uk> said:
>
> > Hello R Users,
> > I am investigating the basic use of the LME function, using the following
> example;
> >
> > Response is Weight, covariate is Age, random factor is Genotype
> >
> > model.lme <- lme (Weight~Age, random=~ 1|Genotype)
> >
> > After summary(model.lme), I find that the estimate of Age is 0.098 with
> p=0.758.
> >
> > I am comparing the above model with the AOV function;
> >
> > model.aov <- aov (Weight~Age + Genotype)
> >
> > I find that the estimate of Age is also 0.098, and p=0.758 as in the LME
> model above.
>
> Have a look at summary(model.lme), find the "Random Effect:"-part and see
> whether the Genotype variation is close to 0. If so, this would explain why
> the estimates are similar, as the random factor Genotype then has almost
> negligible variation.
And, as Brian pointed out (and I'm sure you already know), the
distinctions disappear in an orthogonal design. If the same ages are
recorded for all Genotypes, you get the same results whether you use
lme, lm, aov, or aov with an Error(Genotype) term. Perhaps except for
the DF calculation in lme, but this might be a case it can get right.
--
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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