nat writes:
I want to specify a two-factor model in lme, which should be easy?
Here's what I have:
factor 1 - treatment FIXED (two levels)
factor 2 - genotype RANDOM (160 genotypes in total)
I need a model that tells me whether the treatment, genotype and
interaction terms are significant. I have been reading 'Mixed effects
models in S' but in all examples the random factor is not in the main
model - it is a nesting factor etc to specify the error structure. Here
i need the random factor in the model.
I have tried this:
height.aov-lme(height~trt*genotype,data.reps,random=~1|genotype,na.action=na.exclude)
but the output is nothing like that from Minitab (my only previous
experience of stats software). The results for the interaction term are
the same but F values for the factors alone are very different between
Minitab and R.
This is a very simple model but I can't figure out how to specify it.
Help would be much appreciated.
As background: The data are from a QTL mapping population, which is why
I must test to see if genotype is significant and also why genotype is a
random factor.
Thanks
It seems your message didn't get any replies (at least none
posted to r-help).
I recentely adjusted such a model (two effects, one fixed,
another random, with interaction effects) using lme. I used the
following command:
z1 - lme(reacao ~ posicao,data=memoria,random=~1|subject/posicao)
Where my model is
reacao = mu + posicao (fixed) + posicao*subject (random) +
subject (random)
Beware though that minitab uses different estimation methods (in lme
itself you may use maximum likelihood other restricted m.l) and the
results need not to be the same.
--
Fernando Henrique Ferraz P. da Rosa
http://www.ime.usp.br/~feferraz
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