politzerahless at gmail.com
Sun Jan 26 08:24:36 CET 2014
Have you seen this [admittedly pretty old now] message from the
? My understanding was that it is ok to test interactions in
within-subjects designs, and that you could do it by faking a dataset
that represents the interaction (step 3 in that message) and then
doing a dependent samples t-test. I had never heard before that
interactions can't be tested in a within-subjects design, but also
it's been a long time since I've looked at this issue--I'd definitely
be interested to hear if this is no longer the recommended way to test
interactions. I have seen messages saying that it doesn't work for
between-subjects designs (e.g.
but I'm not sure if that's still current. Hopefully someone on the
list can offer more insight about the second question.
> Message: 2
> Date: Fri, 24 Jan 2014 10:54:10 -0500
> From: Joshua Hartshorne <jkhartshorne at gmail.com>
> To: fieldtrip at science.ru.nl
> Subject: [FieldTrip] interactions
> <CA+3amhe+x4+TNUY1tf0aXe-cf-AB1kTE+ZHTpuRJxNQ=bNioUQ at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
> Hi List!
> I have seen around a dozen comments in the archives that interactions can't
> be tested by permutation for within-subject designs. I haven't been able to
> find a thread that explains why not. It seems like in a 2x2 design, you
> could still pick one of the conditions and permute the labels. I'm sure
> there's a proof somewhere for why this doesn't work, and it would be great
> to see it.
> Similarly, for the mixed design, why permute the between-subject labels?
> Why not permute the within-subject labels instead? Actually, why not do
> both? I follow the reasoning why permuting both is overkill, but not why
> it's wrong.
> If someone could explain, it would be much appreciated. Knowing what to do
> is good, but it would be even better to understand why.
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