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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! Shengwei On 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? > Thanks > All the best, > Anderson > > > On Friday, May 9, 2014, Shengwei Zhang <[log in to unmask]> wrote: > >> 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 >> >