Dear FreeSurfer experts,
I am attempting to disentangle the effects of different features of
pharmacological treatment on cortical thickness.
I am running glmfit from the commandline, with multiple covariates (a.o.
Z_Age, Z_TreatmentDuration and Z_StartAge) in the fsgd-file. These
covariates are correlated up to approximately 0.6 , which to my
understanding is not ideal yet not inducing collinearity. Running glmfit, I
do not get any errors such as ill-designed matrix or so.
My question regards the way the different regression weights are calculated
in each voxel. If I test the variance in CT of voxel A explained by for
example TreatmentDuration, and part of the variance in voxel A is explained
by both TreatmentDuration and StartAge, will the regression weigth of
TreatmentDuration than include the part that is also explained by StartAge?
Or are all other covariates first "regressed out" of the variance, such that
the variable I test can only explain the variance that was not explained by
any of the other covariates?
Thank you very much, your help is very much appreciated!
Best wishes,
Lizanne