Hi Gang,
Thank you for your work on this. We'd like to use 3dLMEr to test functional activation differences between groups during an emotional faces task. There are three groups (ADHD-P, ADHD-D, and ADHD-NA), three emotional trial conditions (pos, neg, neut), and a few covariates we want to include in our model (age, sex, handedness, site, and co-morbidities). Basically, we want to test differences in trial-type activation between groups while controlling for the listed covariates within a specified mask. I looked through the examples in the documentation, but am uncertain about how to set up the "-model" and "-gltCode" parts of the script for our data.
Is this the right idea for how I'd set up this part of the script?
-model 'emotion+group+(1|Subj)+(1|age)+(1|sex)+(1|handedness)+(1|site)+(1|comorbid)'
-gltCode adhd.p 'group : 1*adhd-p' \
-gltCode adhd.d 'group : 1*adhd-d' \
-gltCode adhd.na 'group : 1*adhd-na' \
-gltCode pos 'emotion : 1*pos' \
-gltCode neg 'emotion : 1*neg' \
-gltCode pos 'emotion : 1*neut' \
-gltCode adhd.p-adhd.d 'group : 1*adhd.p -1*adhd.d' \
-gltCode adhd.p-adhd.na 'group : 1*adhd.p -1*adhd.na' \
-gltCode adhd.d-adhd.na 'group : 1*adhd.d -1*adhd.na' \
I think it's this last chunk that I'm most uncertain about. How do I introduce the three emotion conditions into each of the three group differences? Would I end up with 9 total lines for this 3x3 setup?
Huge thanks in advance for your time and help! It's greatly appreciated.
Best,
Amar
