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Hello,

I'm running randomise in the last step of TBSS but not sure how to configure the design matrix using GLM. The _corrp image showed nothing significant, which is unexpected.

The tbss_1 to 4 steps were run successfully. The model used is that FA is linearly related to the a) presence of disease (0 or 1), b) age, c) sex, d) education, e) race (1 or 2), and f) specific brain region volume normalised.

Here's the input to Glm using the latest version of FSL V5.0.6:
1. GLM Setup: "higher level/ non-timeseries design" was chosen, and # inputs equals the number of participants (about 100);
2. "EVs" tag in GLM: # EVs = 7 (6 covariates in previous paragraph and 1 error term), no voxel-dependent EVs, corresponding values were pasted in the order that the participants appeared in the all_FA_skeletonise (for the error term it's all ones);
3. "Contrast & F-tests" tag in GLM: 1 contrast, 0 F-tests, only the covariate of interest (e.g. a or e) set to 1 (assume positive correlation) or -1 (negative correlation) and other EVs set to 0.
4. repeat 1-3 for different covariates of interest and different type of correlation.

Then the design matrix was saved and randomise run.

Is this correct? I read the Fslwiki page about GLM but didn't find the answer. Any help is appreciated.

Shengwei