It is just a standard multiple regression analysis where all regressors are fit simultaneously. One weight does not include that of another weight. doug
On 3/12/14 5:16 AM, L. Schweren wrote:
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
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