Hello Brennan,
if you are specifically interested in the run effect, then this model can be used by adding in an exchangeability blocks file to randomise ( each subject forming a unique “block” ). Alternatively you take take the “final” output of tbss that would be provided to randomise, all_FA_skeletonised, split with fslsplit, calculate each subjects run1-run2 difference image with fslmaths, recombine those outputs with fslmaths as ( e.g. ) all_FA_skeletonised_differences and pas s that to randomise.
Hope this helps,
Kind Regards
Matthew
--------------------------------
Dr Matthew Webster
FMRIB Centre
John Radcliffe Hospital
University of Oxford
> On 21 Jan 2020, at 00:05, Brennan Jackson <[log in to unmask]> wrote:
>
> Hello,
> I am currently following this outline (https://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/fdt1/index.html) to conduct tbss from a set of data consisting of 2 groups of 4 subjects with 2 visits a piece (16 total). I am currently in the process of creating my design matrix based on the ANOVA: 2-groups, 2-levels per subject (2-way Mixed Effect ANOVA) from this webpage: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#ANOVA:_2-groups.2C_2-levels_per_subject_.282-way_Mixed_Effect_ANOVA.29
>
> I think I have successfully created my design.con from the previous link, however, the last portion says fslmaths is required rather than randomise. I am unsure how to subtract the visit images after all of the data has been skeletonised. Which version of the FA maps would I use for fslmaths? (ex. there is FA_to_target, FA_to_target_warp).
>
> In short, I have the design matrix and skeletonised FA, but am unsure how to run statistics using fslmaths. Any help would be appreciated. Thanks!
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