Hi all,
As a start, I am interested in running a general linear model in 3dMVM.
I think I would say that this is a 3 x 2 ANCOVA  although age is a main effect of interest rather than a covariate. I am also controlling for the site in my model (there are two separate sites). Also, I am not interested in the effect of age ONLY on brain response.
Within subject facts: Conditions (equal, overinclude and exclude)
Between subject factors: age, site, and group (risk, HC)
My primary effect of interest: group and group x age differences in brain response during exclusion (exclusion vs. equal) and overinclusion (over vs. equal contrasts) when controlling for site location.
Questions:

Do I have to look at it anyway as I am looking at the interaction term (my understanding is yes based on other statistical tests).

Reporting: When reporting the F statistics in my glf output and my glt output that better explain the directionality of findings  do these outputs correct for site location automatically? Or should I be reporting the group:site:age: condition F value and then the directionality coefficients and tvalues? Do these tvalues/coefficients correct for site? I guess I am still struggling with which values make sense to report in paper.
Also, does this model design in 3dMVM make sense given my research interest? Want to triplecheck that I am doing this all correctly.
Thanks again
#!/bin/bash
3dMVM prefix Feb_2023_rerun_2 \
bsVars "grp*age*site" \
mask /scratch/06953/jes6785/SOBP/CYB_UPDATE_JAN_2023/ATLAS/bin_social_uniformitytest_z_FDR_0.01.nii.gz \
wsVars "condition" \
qVars "age" \
GES \
num_glt 15 \
gltLabel 1 RISKvHCexc_v_equ gltCode 1 'grp : 1*RISK 1*HC condition : 1*exclude 1*equal' \
gltLabel 2 RISKvHC_over_v_equ gltCode 2 'grp : 1*RISK 1*HC condition : 1*over 1*equal' \
gltLabel 3 RISKvHC_over_v_exc gltCode 3 'grp : 1*RISK 1*HC condition : 1*over 1*exclude' \
gltLabel 4 RISK_over_v_exc gltCode 4 'grp : 1*RISK condition : 1*over 1*exclude' \
gltLabel 5 HC_over_v_exc gltCode 5 'grp : 1*HC condition : 1*over 1*exclude' \
gltLabel 6 RISK_exc_v_equ gltCode 6 'grp : 1*RISK condition : 1*exclude 1*equal' \
gltLabel 7 HCexc_v_equ gltCode 7 'grp : 1*HC condition : 1*exclude 1*equal' \
gltLabel 8 RISKover_v_equ gltCode 8 'grp : 1*RISK condition : 1*over 1*equal' \
gltLabel 9 HCexc_v_equ gltCode 9 'grp : 1*HC condition : 1*over 1*equal' \
gltLabel 10 RISKvHC_exc_v_equ_age gltCode 10 'grp : 1*RISK 1*HC condition : 1*exclude 1*equal age :' \
gltLabel 11 RISKvHC_over_v_equ_age gltCode 11 'grp : 1*RISK 1*HC condition : 1*over 1*equal age :' \
gltLabel 12 HC_exc_v_equ_age gltCode 12 'grp : 1*HC condition : 1*exclude 1*equal age :' \
gltLabel 13 RISK_exc_v_equ_age gltCode 13 'grp : 1*RISK condition : 1*exclude 1*equal age :' \
gltLabel 14 HC_over_v_equ_age gltCode 14 'grp : 1*HC condition : 1*over 1*equal age :' \
gltLabel 15 RISK_over_v_equ_age gltCode 15 'grp : 1*RISK condition : 1*over 1*equal age :' \
num_glf 4 \
glfLabel 1 EXC_RISKvHCexc_v_equ glfCode 1 'grp : 1*RISK 1*HC condition : 1*exclude 1*equal' \
glfLabel 2 RISKvHC_OVER_v_equ glfCode 2 'grp : 1*RISK 1*HC condition : 1*over 1*equal' \
glfLabel 3 RISKvHC_exc_v_equ_AGE glfCode 3 'grp : 1*RISK 1*HC condition : 1*exclude 1*equal age :' \
glfLabel 4 RISKvHC_exc_v_equ_AGE glfCode 4 'grp : 1*RISK 1*HC condition : 1*over 1*equal age : ' \