Dear AFNI team (Gang!)
I hope you're all keeping safe and well.
I wanted to ask for your advice on modelling between-subjects effects in 3dLMEr.
I have a dataset where participants listen to a story twice. On the second listening, the story is either temporally scrambled at the sentence or word level.
I'd like to contrast the within-subject effects of the intact vs scrambled versions of the story. Further, I'd also like to contrast the between-subjects effects of listening to the sentence (long) vs word (short) scrambled versions of the story.
I've specified the model and post-hoc GLTs as follows, but I'm concerned that 3dLMEr may not account for differences in group variance between groups that listened to the short vs long scrambled versions of the story. Please could you advise as to whether my model specification here is sufficient?
-model 'Age+Gender+scram+(1|Subj)' \
-qVars "Age" \
-qVarsCenters 20.66 \
-gltCode intact 'scram : 1*intact' \
-gltCode longscram 'scram : 1*long' \
-gltCode shortscram 'scram : 1*short' \
-gltCode intactVscram 'scram : 1*intact -0.5*long -0.5*short' \
-gltCode intactVlong 'scram : 1*intact -1*long' \
-gltCode intactVshort 'scram : 1*intact -1*short' \
-gltCode longVshort 'scram : 1*long -1*short' \
-dataTable \
Subj Age Gender scram InputFile \
