Hi Kevin,

Doubling is a bad idea. You can do this in PALM: Make the design as usual, but include subject-specific intercepts for all those that have two measurements, that is, include one EV per subject that is all-zeroes, except that it contains +1 for one run and -1 for the other run.

Then define multi-level exchangeability blocks: one block per subject in one level. In the level above, one block for all subjects with one run (so these subjects can be permuted with each other), and one block for all subjects with two runs (likewise, these subjects can be permuted with each other). Finally, a top-level that prevents shufflings (with a negative sign in front of it).

There is no need for variance groups.

Hope this helps!

All the best,

Anderson

On 17 August 2017 at 12:55, Kevin Japardi <[log in to unmask]> wrote:

Hello FSL experts!

If I had an fMRI dataset, where each participant performed the same task twice, I would normally run a 3-stage Feat analysis, where my second level looked at the mean activation across tasks per subject.

If I had a subject who only performed the task once, but wanted to include their data into the group analyses, how would it be possible to add them into a 3rd level GFeat if the input options are to use a lower level feat or higher level cope file?

Could a possibility be to double their single run data into a 2nd level GFeat, but only look at activation within one run? Would anything differ if I were to look at mean activation across the same run twice? (input = the same run, and your model includes both runs)

Any input would be greatly appreciated!

Thank you,
Kevin Japardi