Hi again Dav,
> The one thing that still seems to be a bit of an issue is whether I
> can correct for multiple contrasts, for example, if I have 1
> contrast of interest, or 2 or 100 (in theory only!). If I do higher-
> level contrasts independently for just 1 contrast vs. 100, I am
> nearly guaranteed to get spurious significance in the latter case.
> In my case, I have a handful of contrasts (which are actually
> largely independent - along the lines of modelling 3 two-level
> factors and the interactions between them). Thus, I am still a
> little concerned about correcting for these multiple (but at least
> partially independent) contrasts.
>
> Or is this handled already by those contrasts having been specified
> simultaneously at the first two levels?
this is something that is, funnily enough, largely ignored in
neuroimaging. If you ask a question through some contrast and
threshold the resulting SPM at a FWE-rate (i.e. corrected for multiple
comparisons among the voxels in that SPM) of 0.05 you basically say
that you accept 1 false positive out of every 20 times you test a
contrast.
If you use two different contrasts in the same data the false positive
rate pretty much doubles, for the experiment as a whole. And so it
goes as you keep coming up with more contrasts.
So you are right that in your average neuroimaging paper the false
positive rate is typically much higher than 0.05, for the paper/study
as a whole.
This is very easy for you to "fix" yourself. Let's say you are doing a
study where you want to test four different contrasts. Test them at a
0.05/4 FWE level instead, and you will have a false positive rate of
0.05 for your paper/study.
Chances are you'll report fewer blobs though ;-)
Good luck Jesper
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