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Dear SPM experts
I identified significant different regions among three groups (for example,saying three groups as 'A', 'B', and 'C') performing voxel-wise one-way ANOVA with using SPM8 software. So I want to do post-hoc pair-wise t-test between 'A' and 'B', between 'B'
and 'C', and between 'C' and 'A'.
So I have some questions.
1) Should I perform these post-hoc t-test to whole brain? Or should I perform them to the only region which is identified as significantly different by the ANOVA analysis?
If it is a true post hoc test it must be done using the regions identified as significant in the ANOVA. If you re-run the whole brain analysis it has no relationship to the ANOVA and thus is not a post-hoc test, but a new series of tests.
There are a few possible approaches. Run the t-tests and mask with the significant ANOVA findings, or extract beta values for each person from the significant clusters from the F-test, and do group comparisons on those. The second option may be best, as you are now running 1 simple t-test for each comparison for each cluster. However, be aware of the difference, as this approach tests "overall in this cluster does group A differ from B". And this may have issues. For example in a large cluster if group A > B in some parts but B > A in others. It is not always fair to assume that all voxels in a large cluster will show the same effect. So if you have large clusters, whole brain t-test masked with the F-stat may be best.
Likewise I think you should avoid choosing a small ROI around the 'peak' of each cluster, as that is a somewhat biased result (running post-hoc tests only on regions showing the greatest effect, you have a circularity problem).
2) When I perform these post-hoc t-test, should I adopt bonferroni corrected p-value? (say, 0.05/3 in this case).
Yes, absolutely. Some form of correction (bonferroni or otherwise) is necessary. But keep in mind that bonferroni may be overly stringent. If, for example, your F-test gives 4 significant clusters, you are now running at least 12 post hoc comparisons (3 t-tests in each of the 4 clusters), and need a large correction. Consider FDR correction instead.
3) If areas of the significant region with the post-hoc t-test is larger than those of the significant region with the ANOVA,
how should I interpret those regions outside of the region identified by the ANOVA?
Shouldn't be an issue as you should not run whole brain t-tests here, see above. But, if you did it, it's easy to interpret: The ANOVA is one statistic, a whole brain t-test is a different statistic, and they will never perfectly overlap. They may be sensitive to different things. Which you prefer depends on how you want to answer your question, but if you are looking for 'overall differences between groups', then the ANOVA is a likely the more correct approach.
I hope that helps.
Colin Hawco, PhD
Neuranalysis Consulting
Neuroimaging analysis and consultation
www.neuranalysis.com
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