Hi-

OK, so the issue does appear to be that: the F-stat clusterizing misses out on signedness, which the bi-sided clusterizing with the t-stat uses. Running 2-sided clusterizing with the t-stat gave the same results as the F-stat clusterizing.

Here were the 3 clusterize commands via the command line (and I use the 1sided ->right tail clusterizing on the F-stat, which would be the same as 2sided, because the stat is positive definite), with output cluster maps of ROIs in each case, as well as the thresholded data subvolumes:

# 1-sided F-stat
3dClusterize                                                                 \
    -nosum                                                                   \
    -1Dformat                                                                \
    -inset       MVM_emx_baseline_splitBLOCK_L_Cov_AgenSex_batchomit.nii     \
    -idat        1                                                           \
    -ithr        1                                                           \
    -NN          3                                                           \
    -clust_nvox  6                                                           \
    -pref_map    clust_map_F_1sided.nii.gz                                   \
    -pref_dat    clust_dat_F_1sided.nii.gz                                   \
    -1sided      RIGHT 4.13

# bi-sided t-stat
3dClusterize                                                                 \
    -nosum                                                                   \
    -1Dformat                                                                \
    -inset       MVM_emx_baseline_splitBLOCK_L_Cov_AgenSex_batchomit.nii     \
    -idat        10                                                          \
    -ithr        11                                                          \
    -NN          3                                                           \
    -clust_nvox  6                                                           \
    -pref_map    clust_map_t_bisided.nii.gz                                  \
    -pref_dat    clust_dat_t_bisided.nii.gz                                  \
    -bisided     -2.0322 2.0322

# 2-sided t-stat
3dClusterize                                                                 \
    -nosum                                                                   \
    -1Dformat                                                                \
    -inset       MVM_emx_baseline_splitBLOCK_L_Cov_AgenSex_batchomit.nii     \
    -idat        10                                                          \
    -ithr        11                                                          \
    -NN          3                                                           \
    -clust_nvox  6                                                           \
    -pref_map    clust_map_t_2sided.nii.gz                                   \
    -pref_dat    clust_dat_t_2sided.nii.gz                                   \
    -2sided      -2.0322 2.0322

I compared the F-stat cluster maps with each of the t-stat ones:
+ F-stat clusters are different than bi-sided t-stat clusters

$ 3dDiff -a clust_map_F_1sided.nii.gz -b clust_map_t_bisided.nii.gz
++ Images differ: 84 of 53248 elements differ ( 0.16%)

+ F-stat clusters are the same as 2-sided t-stat clusters

$ 3dDiff -a clust_map_F_1sided.nii.gz -b clust_map_t_2sided.nii.gz
++ Images do NOT differ

In the end, using the bi-sided t-stat clusters seems most appropriate. The loss of sign information with the F-stat comparison means that is a poorer check. The fact that the 2-sided t-stat matches the F-stat one just means that the interpretation of what is happening seems consistent (-> that the difference is due to ignoring signs in the data).

--pt



Edited 1 time(s). Last edit at 03/09/2023 01:28PM by ptaylor.