Here is some toy data to give an example. Imagine someone is test-riding
several bicycles to decide which to buy, and measures their average speed
during each test-ride. They want to assess the main effects and interaction
of brand and material on speed.
Speed Size Brand Material
20 small giant steel
25.1 medium giant steel
25.2 medium trek aluminum
26 small cannondale carbon
19.9 large giant aluminum
21 medium trek carbon
30 medium cannondale carbon
This is the output I get:
> fit = aov(Speed~Brand*Material, data=myData)
> summary(fit)
Df Sum Sq Mean Sq F value Pr(>F)
Brand 2 49.862 24.931 2.3738 0.2964
Material 2 13.502 6.751 0.6428 0.6087
Residuals 2 21.005 10.503
I suppose I am missing something very obvious here as to why the interaction
is not reported, but I don't see what it is.
Cheers,
Gabe
On Wed, Apr 8, 2009 at 1:34 PM, Patrick Connolly <p_conno...@slingshot.co.nz
> wrote:
> On Wed, 08-Apr-2009 at 12:59PM -0700, Gabriel Murray wrote:
>
> |> I've noticed with certain datasets that when I try to do an anova and
> test
> |> for main effects and interaction for two explanatory variables,
> sometimes
> |> the main effect results are given but not the interaction results. For
> |> example,
> |>
> |> ex1 = aov(Score ~ var1*var2, data=myData)
> |> summary(ex1)
>
> Could it be that there are no degrees of freedom left?
>
> That's about my best guess without enough information.
>
>
> |> ______________________________________________
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> |> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> |> and provide commented, minimal, self-contained, reproducible code.
>
>
> Nothing you sent is reproducible.
>
>
> --
> ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.
> ___ Patrick Connolly
> {~._.~} Great minds discuss ideas
> _( Y )_ Average minds discuss events
> (:_~*~_:) Small minds discuss people
> (_)-(_) ..... Eleanor Roosevelt
>
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