Dear Gang,

Sorry -- I replied to the wrong post.. I just attached the same post as a follow-up to your suggestion.

Thanks a lot for the suggestion. I see that centering would be a good option to remove the session effect (which is a within-ss covariate). I just have a few follow-up questions:
1) But for between-ss covariates, it is ok to residualize it (e.g., body mass on RT in case if the covariate is related to the overall grand mean across subjects)? Since the between-ss covariates still preserve the subject-wise differences, I presume it might be something similar to centering across subjects?
2) Would you still recommend using 3dLME framework after I center RTs or other ones like 3dMVM? My model specification for 3dLME is following:
y (brain) ~ treatment * cue * RT (centered) + body mass + session order + (1|subj)
-gltLabel 1 ‘DD_RT’ -gltCode 1 ‘treatment : 1*DD RT : ’ \
-gltLabel 2 ‘PC_RT’ -gltCode 2 ‘treatment : 1*PC RT : ’ \
-gltLabel 3 ‘treatment_x_RT’ -gltCode 3 ‘treatment : 1*DD -1*PC RT : ’ \

OR without any COVs:
y (brain) ~ treatment * cue * RT (centered) + (1|subj)…
and same GLTs as above.


Thank you so much for your help again. I really appreciate it.
Best, Michelle.