Hello,

Please can you advise whether I have set up covariates correctly for a GLM 2nd level analysis.

Covariates of interest:
AllSubjects [1,1,1,1,1....1,1,1]
Patients [1,1,1,1.......0,0,0]
Controls [0,0,0,0.......1,1,1]
Test_1 [-6.75, 0.18, -4.25.....]
Test_2 [-0.63, 0.92, -1.46,.....]

Control covariates:
Age (demeaned) [3.16, 10.16, -9.56.....]
Education (demeaned)  [-0.33, 4.66, -2.33,....]
Gender [-0.5, -0.5, 0.5, 0.5,....]

All covariates also have a sub-group version e.g. Test_1_Patients, Gender_Controls.

Question 1:
The test scores, for each test, are normalised based on a population sample matched for education, gender & age (i.e., the score for person 1 and person 2 may have been normalised based on different populations. Formula score - population mean / population SD). In this case zero is meaningful. Do these need to be further normalised at a whole group level?

Question 2:
Are the control convariates set up correctly? I have read conflicting items on how to set up gender.

Question 3:
I have selected semi-partial correlations for ROI-to-ROI investigation.

One analysis is set up as:
Test_1_Controls > Test_1_Patients; one-sided positive
[0,0, -1, 1, 0, 0, 0] referring to [Patients, Controls, Test_1_Patients, Test_1_Controls, Gender, Age, Education]

Is it correct to say that this set up is testing whether in relation to Test_1 controls show higher ROI-to-ROI functional connectivity compared to patients while controlling for gender, age and education?

Thank you in advance for any assistance.

Therese