Hi Alfonso,

Thanks for your reply.

I did the first approach:

"1) first define a new set of second-level covariates where the missing subject data is filled with 0's in all of the covariates that are relevant to your analysis (e.g. create a new 'AllSubjects_valid' covariate and a new 'IQ_valid' covariate, where the values for the missing subject have been filled with 0). Then perform the standard second-level analysis using these new covariates (e.g. select 'AllSubjects_valid' and 'IQ_valid' and enter a contrast [0 1])"

... and I think I know where the source of error was upon reading it more carefully this time.

I created a new 'AllSubjects_valid' covariate, where I fill in 0s for subjects that I want to exclude. However, I did not create corresponding covariates (e.g., a new 'IQ_valid' covariates with 0s for subjects to be excluded) for all other behavioral measures.

If I choose to do approach (3) instead, would I have to input NaN for all second-level covariates, or does CONN recognizes that a subject be excluded as long as it has one NaN for any of the covariates?

Thanks!

Best,
Darren