I have one statistic question:
Say I have a within-subject repeated measure design, with two conditions A and V, I want to test if there are any regions more involved in A comparing to it in V.
Two approaches in my mind:
each condition has one regressor in the first level GLM matrix, resulting in beta for A and beta for V, for group level analysis, do paired t-test to test the difference of beta-A against beta-V. (i.e. the example script s5.ttest.paired in AFNI_data6/group_results)
add a -gltsym ‘SYM: A -V’ -glt_label 1 A-V, to test the difference of A against B at subject level, resulting one beta indicating the difference, then do one-sample t-test to test this difference beta value against zero.
Could you share your mind on this topic, which approach is more recommended, or it depends on different conditions?