...
>> Back to the fMRI data. Imagine a purely within-subject 3x3-ANOVA,
>> which should be reasonable nowadays. E.g. something like "face"
>> (happy, sad, fearful), and "sex" (male, female, morph). Maybe I
>> have specific hypotheses, but maybe I do not (at least for some
>> levels, e.g. concerning "morph"). In the latter case, I would run
>> F-tests for "face", "sex" and the interaction. Imagine I get some
>> clusters surpassing an otherwise defined voxel-size threshold. What
>> should I do then?
>
> (1) If you get an interaction, you should exclude those voxels from
> the effects of face and sex.
> (2) You can use a mask to constrain the analysis within face or sex or
> the interaction, but do not use SVC. SVC adjusts for a smaller search
> region.
>
> Imagine, hypothetically, that I said any cluster with a p-value of .2
> was significant for a main effect. Now I look in those clusters and
> finds clusters that are p<0.05 for individual tests because I use
> small-volume correction. You've biased yourself towards finding a
> group difference. While the case is true that a significant F-test
> means that you will have at least 1 significant pst-hoc t-test, it
> does not mean that you have any more than one significant post-hoc
> t-test. Thus, the reduction in search volume and using SVC can lead to
> false positives.
I agree with you SVC on the F cluster would make no sense. You might
as well use uncorrected p's in the t tests. To follow the planned
comparison approach, you'd need to correct both the F and the t tests
for the whole volume.
Best wishes,
Roberto Viviani
Dept. of Psychiatry III
University of Ulm, Germany
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