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