I don't understand: I just ran the first example in the "aov"
help
page, and it produced F ratios and p values.
If this does not answer your question, I suggest you read Pinheiro
and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer) if you
haven't already and try to use lme for what you want. If all your
applications are perfectly balanced, then aov may be fine for you.
However, the function "aov" codified routine practice for this kind of
problem as of ~1980. However, there have been substantive developments
in this area since then, and Pinheiro and Bates is the best reference I
know on both the theory and the application -- as of 2000.
hope this helps.
spencer graves
David Semmens wrote:
> I would like to know if there is a way of directly calculating the
> F-ratio of a random effect using the "aov" function. I have 2
factors
> in my model, "population" which is random and "length"
which is the
> length of female fish within each population. The dependent variable is
> "diam" which is the average diameter of eggs produced by each
female.
> At present I set up the model like this:
>
> >model <- aov(diam~population*length, data=data)
> >anova(model)
>
> then using the output:
>
> >ratio=MS-population/MS-interaction
> >1-pf(ratio, df-population,df-interaction)
>
> Is there a way of getting r to calculate the correct F-ratio for a
> random factor and present it in the original output?
>
> Thanks,
> David Semmens.
>
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