Hello,
Recently we have started to spatially constrict the data we input into our 3dANOVA2 mixed effect script.
Our original intent was to only include voxels that were significant in our main effect maps (A and B) from a previously run ANOVA so as to avoid subtractions (A - B) that lead to activation that was neither active in main effect A nor B.
What we found was that when we masked out any non-main effect A and B activity in datasets just prior to the ANOVA (%signal change Gaussian blurred data), we received different ANOVA results in each individual voxel. The difference was slight, but counter intuitive as I thought the ANOVA programs in afni processed on a voxel by voxel basis and there was no spatial variance pooling or anything of that sort.
Based on your more in depth understanding of the math behind the 3dANOVA programs is there any reason that spatially constricting input should affect the output?
Thanks so much for your time!
Jeremy