Hi Anderson,Here's the link with all the information:
https://drive.google.com/file/d/0B1-hPZ22Vq1VOHRtaGZydDVsLUk/edit?usp=sharing
The randomise command was:randomise -i all_FA_skeletonised -o tbss -m mean_FA_skeleton_mask -d design.mat -t design.con --T2
Thank you!ShengweiOn Sat, May 10, 2014 at 6:25 AM, Anderson M. Winkler <[log in to unmask]> wrote:Hi Shengwei,Could you please attach the design files (.mat, .con, etc) and paste here the exact randomise call you're using?ThanksAll the best,Anderson
On Friday, May 9, 2014, Shengwei Zhang <[log in to unmask]> wrote:
Is this correct? I read the Fslwiki page about GLM but didn't find the answer. Any help is appreciated.Then the design matrix was saved and randomise run.4. repeat 1-3 for different covariates of interest and different type of correlation.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 0.2. "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);1. GLM Setup: "higher level/ non-timeseries design" was chosen, and # inputs equals the number of participants (about 100);Here's the input to Glm using the latest version of FSL V5.0.6: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.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.
Shengwei