I am very new to R and thus find those examples a bit confusing although I
believe the solution to my problems lies there.
Lets take for example an experiment in which I had two between subject
variables - Strain and treatment, and one within - exposure. all the
variables had 2 levels each.

I found an interaction between exposure and Strain and I want to compare
Strain A and B under every exposure (first and second).
The general model was with that function:
aov(duration~(Strain*exposure*treatment)+Error(subject/exposure),data)

in summary(aovmodel) there was a significant interaction between exposure
and strain.
how (using those HH packages) can I compare Strains under the conditions of
exposure?


BTW - I don't have to use aov (although its seems to be the simplest one).

Thank you very much.


On Mon, Dec 21, 2009 at 12:16 AM, Richard M. Heiberger <rmh@temple.edu>wrote:

> For simple effects in the presence of interaction there are several
> options included in the HH package.  If you don't already have the HH
> package, you can get it with
>  install.packages("HH")
>
> Graphically, you can plot them with the function
>  interaction2wt(..., simple=TRUE)
> See the examples in
>  ?HH::interaction2wt
>
> For tests on the simple effect of A conditional on a level of B, you
> can use the model formula B/A and look at the partition of the sums of
> squares using the split= argument
>  summary(mymodel.aov, split=<put your details here>)
>
> For multiple comparisons from designs with Error() terms, you need to
> specify the same sums of squares with an equivalent formula that doesn't
> use the Error() function.  See the maiz example in
>  ?HH::MMC
> Read the example all the way to the end of the help file.
>
> Rich
>
>

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