| palm
-i dr_stage2_ic0000.nii.gz -i dr_stage2_ic0001.nii.gz -i
dr_stage2_ic0002.nii.gz -i dr_stage2_ic0003.nii.gz -i dr_stage2_ic0004.nii.gz
-i dr_stage2_ic0005.nii.gz -i dr_stage2_ic0006.nii.gz -i
dr_stage2_ic0007.nii.gz -i dr_stage2_ic0008.nii.gz -i dr_stage2_ic0009.nii.gz
-i dr_stage2_ic0010.nii.gz -i dr_stage2_ic0011.nii.gz -i
dr_stage2_ic0012.nii.gz -i dr_stage2_ic0013.nii.gz -i dr_stage2_ic0014.nii.gz
-i dr_stage2_ic0015.nii.gz -i dr_stage2_ic0016.nii.gz -i
dr_stage2_ic0017.nii.gz -i dr_stage2_ic0018.nii.gz -i dr_stage2_ic0019.nii.gz
-i dr_stage2_ic0020.nii.gz -i dr_stage2_ic0021.nii.gz -i
dr_stage2_ic0022.nii.gz -i dr_stage2_ic0023.nii.gz -i dr_stage2_ic0024.nii.gz
-i dr_stage2_ic0025.nii.gz -i dr_stage2_ic0026.nii.gz -i
dr_stage2_ic0027.nii.gz -i dr_stage2_ic0028.nii.gz -i dr_stage2_ic0029.nii.gz
-i dr_stage2_ic0030.nii.gz -i dr_stage2_ic0031.nii.gz -i
dr_stage2_ic0032.nii.gz -i dr_stage2_ic0033.nii.gz -i dr_stage2_ic0034.nii.gz
-i dr_stage2_ic0035.nii.gz -corrmod -noniiclass -o try6_liststg2 COMMAND 2: with different parameters in red |
| palm
-i dr_stage2_ic0000.nii.gz -i dr_stage2_ic0001.nii.gz -i
dr_stage2_ic0002.nii.gz -i dr_stage2_ic0003.nii.gz -i dr_stage2_ic0004.nii.gz
-i dr_stage2_ic0005.nii.gz -i dr_stage2_ic0006.nii.gz -i
dr_stage2_ic0007.nii.gz -i dr_stage2_ic0008.nii.gz -i dr_stage2_ic0009.nii.gz
-i dr_stage2_ic0010.nii.gz -i dr_stage2_ic0011.nii.gz -i
dr_stage2_ic0012.nii.gz -i dr_stage2_ic0013.nii.gz -i dr_stage2_ic0014.nii.gz
-i dr_stage2_ic0015.nii.gz -i dr_stage2_ic0016.nii.gz -i
dr_stage2_ic0017.nii.gz -i dr_stage2_ic0018.nii.gz -i dr_stage2_ic0019.nii.gz
-i dr_stage2_ic0020.nii.gz -i dr_stage2_ic0021.nii.gz -i
dr_stage2_ic0022.nii.gz -i dr_stage2_ic0023.nii.gz -i dr_stage2_ic0024.nii.gz
-i dr_stage2_ic0025.nii.gz -i dr_stage2_ic0026.nii.gz -i
dr_stage2_ic0027.nii.gz -i dr_stage2_ic0028.nii.gz -i dr_stage2_ic0029.nii.gz
-i dr_stage2_ic0030.nii.gz -i dr_stage2_ic0031.nii.gz -i
dr_stage2_ic0032.nii.gz -i dr_stage2_ic0033.nii.gz -i dr_stage2_ic0034.nii.gz
-i dr_stage2_ic0035.nii.gz -d ../GLM_22.mat -t ../GLM_22.con -n 2000 -corrcon – corrmod
-noniiclass -o try7_liststg2glm22_corrcon_2000 MY GLM Looks like so: Higher-level/non-timeseries design # inputs: 22 General Linear Model: EVs Number of main EVs: 2 Number of additional, voxel depended Evs: 0 Group EV1 EV2 TD DCD 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 Contrasts & F-tests Contrasts:4 F-tests: 0 TITLE EV1 EV2 C1 TD>DCD 1 -1 C2 DCD>TD -1 1 C3 TD MEAN 1 0 C4 DCD MEAN 0 1 |
Hi all,I am looking into doing a multiple comparisons correction after running dual regression with 5000 permutations on pediatric functional connectivity data with a low power. Bonferroni correction is not a great choice for me because it is quite conservative and I only have 22 participants total (11 in each group).I am looking into cluster-extent based thresholding however, from what I am reading on your support page, it is redundant to try to cluster when using tfce files.Does anyone have any tips or tricks for me? Is there another option that I should be looking into or should I continue to pursue clustering?Thank you for your time,Noelle Dalin