Hi Alfonso, 

After posting my last question, I have figured out how to look at the contribution of each of my clinical variables alone. I now have a question regarding whether my data are corrected for multiple comparisons, at the post hoc level. 

To remind you....I am using a multivariate F test (bivariate regression) to look at how 4 clinical variables (C1, C2, C3 and C4) can predict FC in a number of regions of interest.

I selected 'ASD' 'C1' 'C2' 'C3' 'C4' and entered [0 1 0 0 0; 0 0 1 0 0; 0 0 0 1 0; 0 0 0 0 1] in the between subjects contrast. Then, after importing values, and navigating to the tools calculator, because I have multiple source ROIs, I selected them all simultaneously to appropriately control for the amount of comparisons.

I now have several main effects, however, in order to see where these main effects are coming from , I am looking at the simple main effect of each of my clinical variables alone by selecting "ASD" and "C1" and entering the contrast [0, 1] in the tools calculator window. I am wondering if I need to apply additional correction here by using the Bonferroni correction and dividing my p value by the number of comparisons (i.e., outcome variables) I have?

Additionally, if I see a significant main effect, but when examining the simple main effect, it does not meet significance with the Bonferroni correction - how can I interpret this? 

Thank you as always, 

Jenna