Dear FSL Users,
I'm wondering on the proper way to generate the design and contrast matrix to perform a Two-sample unpaired t-test with covariates using randomise.
I have 52 subjects (18 controls and 34 patients), and I want to test for differences between groups, while controling for age and gender.
I merged the 52 volumes in a single file (the first 18 volumes are the controls and the rest is the patients).
I've read here (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Two_Groups_with_continuous_covariate_interaction) that the covariates should be demeaned. I've created the following design.mat file, where the 1st column describes the group effect, the second the demeaned age and the 3rd the demeaned gender. The demeaned age is the subject's age minus the mean age of all subjects. The gender is 1 for males, 0 for females. As I have 20 males, the mean gender is 0.384615384615, which I subtract to each subject's value:
/NumWaves 4
/NumPoints 52
/PPheights 1.000000e+00 1.000000e+00
/Matrix
1 0 -5.51923076923 0.615384615385
1 0 -13.5192307692 0.615384615385
...
1 0 -9.51923076923 -0.384615384615
1 0 0.480769230769 -0.384615384615
0 1 -1.51923076923 -0.384615384615
0 1 2.48076923077 -0.384615384615
...
0 1 14.4807692308 -0.384615384615
0 1 -12.5192307692 0.615384615385
And the following design.con file to test for differences between groups:
/ContrastName1 controls > patients
/ContrastName2 controls < patients
/NumWaves 4
/NumContrasts 2
/PPheights 1.000000e+00 1.000000e+00
/Matrix
1 -1 0 0
-1 1 0 0
Is this correct ? Am I missing something with the files or the volumes ? All volumes were registered to the MNI space before merging all subjects.
If I run TFCE, I get a warning because "tfce has detected a large number of integral steps. This operation may require a great deal of time to complete". I've read that this might be due to an error in the design matrix.
TFCE runs without warning if I ***don't*** demean the age and gender columns (ie I put the subject's real age and 0 or 1 for the gender). Would this be correct even if the GLM guide states that covariates should be demeaned ?
There is also the -D option in randomise. Should I use it if I use a design matrix without demeaning the covariates ?
Thanks for your help !
David
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