Hi all,

I am running a within-subjects analysis and would like to examine the effect of a covariate at each level of the Valence factor (2 levels). I have centered the "Change" and "Rating" covariates of interest for each level of Valence separately. Thus, I am wondering whether I need to specify the covariate center for each level or if I can leave it blank. It seems that since I have already removed the mean from them separately that I wouldn't need to include the mean value, right?

So I should be using gltCode 3 and 4 as seen below?

3dLME -prefix 3dLME_Valence*Change*State*Rating \
-mask "/Volumes/Research/CLPS_Amso_Lab/Andrew/FYP/MRI/mask/mask75mni+tlrc.BRIK" \
-model 'Valence*Change*State*Rating' \
-qVars "Change,Accuracy,State,Rating,Age,CB" \
-qVarCenters '0.0016,0.0016,34.75,0.0008,21.67,1.54' \
-num_glt 4 \
-gltLabel 1 'Positive-ChangeEff_cent' -gltCode 1 'Valence : 1*Positive Change : -3.42' \
-gltLabel 2 'Negative-ChangeEff_cent' -gltCode 2 'Valence : 1*Negative Change : 3.25' \
-gltLabel 3 'Positive-ChangeEff' -gltCode 3 'Valence : 1*Positive Change : ' \
-gltLabel 4 'Negative-ChangeEff' -gltCode 4 'Valence : 1*Negative Change : ' \
-ranEff '~1' \
-SS_type 3 \
-jobs 6 \
-dataTable \
Subj Valence Change Accuracy State Rating Age CB InputFile \
3086 Positive 9.42 0.37 47 -1.625 18.47 1 ${rd}/data/brain/orig/3086/3086_glm_bucket+tlrc.BRIK[2] \
3097 Positive -6.58 9.37 28 0.375 29.65 1 ${rd}/data/brain/orig/3097/3097_glm_bucket+tlrc.BRIK[2] \
3155 Positive -0.58 3.87 31 0.375 18.65 1 ${rd}/data/brain/orig/3155/3155_glm_bucket+tlrc.BRIK[2] \
.
.
.

3250 Negative -0.25 -5.75 20 1.46 20.02 2 ${rd}/data/brain/orig/3250/3250_glm_bucket+tlrc.BRIK[2] \
3251 Negative 12.75 -4.75 24 0.46 19.95 2 ${rd}/data/brain/orig/3251/3251_glm_bucket+tlrc.BRIK[2] \
3308 Negative -3.25 -2.65 31 -0.54 19.33 2 ${rd}/data/brain/orig/3308/3308_glm_bucket+tlrc.BRIK[2]