On 7/24/17 4:12 PM, Jiahe Zhang wrote:
No idea. You can try running it with --cwp 1 --no-sim perm.abs.1.3. The --cwp 1 will force it to report all clusters. If that comes up empty (and there are voxels that survive at 1.3, then something is wrong).That makes sense. And thanks for the suggestion! I tried running permutation test with the following command:
mri_glmfit-sim --glmdir r_PCC_glm --sim perm 10000 1.3 perm.abs.1.3 --sim-sign abs
The results are empty maps for all the contrasts I have, which I did not expect, since some of the contrasts are simply testing group mean against 0. Any clue why that might be?
This is a separate simulation, unfortunately.
Also, if I want to run one-tailed test using 'pos', how do I rewrite the above command to include the no-sim part? This didn't seem to work:mri_glmfit-sim --glmdir r_PCC_glm --sim perm 10000 1.3 perm.pos.1.3 --sim-sign pos --no-sim perm.abs.1.3
On Wed, Jul 19, 2017 at 3:21 PM, Douglas Greve <greve@nmr.mgh.harvard.edu> wrote:
______________________________Yes, that is expected with your command line. The issue is that you are using a positive (pos) a priori hypothesis about the sign of the effect. By default, freesurfer generates unsigned statistics (this is what you see when you just view the stats map). When you specify pos, it adjusts the voxel-wise sig value to that of the (lower) signed test, so you see more voxels.
btw, the cluster forming threshold that you are using (1.3 = p<.05) is too small for GRF. Probably you need something like 3 (p<.001). If you want to use 1.3, then use permutation.
On 7/19/17 2:56 PM, Jiahe Zhang wrote:
Here is the command:Dear Freesurfer experts,I'm trying to run multiple comparisons correction using mri_glmfit-sim. Since I'm working with volume data, I used -grf instead of -cache. The resulting map has bigger clusters with higher significance values than the original sig.mgh map from mri_glmfit. Is this normal? Is there anything I should change in my command?
mri_glmfit-sim --glmdir r_PCC_glm --grf 1.3 pos --cwp 0.05 --2spaces
Thanks,
Jiahe
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