lmFit/mrlm output is vastly easier to work with, when you are dealing with
enormous numbers of regressions, in my opinion (having forgotten this
recently and used anova() on a high-dimensional mlm object from base R).

note that eBayes is independent of lmFit, which is the function that most
closely maps to anova(lm(foo ~ bar*baz)) in base R.  If you have a reason to
believe that there is a tractable distribution for the variance across all
the responses you are fitting, eBayes is an enormous advantage.  But it has
nothing fundamentally to do with the speed and manageability advantage that
comes from using lmFit() (or mrlm(), if memory serves -- a robust version).

so:

1) eBayes is not analogous to anova(lm(y~x)); lmFit() and mrlm() do that
job.
2) lmFit() and mrlm() have significant practical advantages over base R
lm().

All of this is simply IMHO, of course.


On Mon, Aug 22, 2011 at 2:42 AM, carol white <wht_crl@yahoo.com> wrote:

> Hello,
> Is there any preference for eBayes in Limma package to the anova R
> function? In addition to moderate t-test, is there any other feature that
> differentiate these two functions?
>
> Cheers,
>
> Carol
>
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-- 
If people do not believe that mathematics is simple, it is only because they
do not realize how complicated life is.
John von Neumann<http://www-groups.dcs.st-and.ac.uk/~history/Biographies/Von_Neumann.html>

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