Hello,
If you want to properly correct over multiple contrasts, then it’s probably best to use PALM ( https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM ) instead of randomise.
Hope this helps,
Kind Regards
Matthew
> On 13 Apr 2017, at 11:20, Blazej Baczkowski <[log in to unmask]> wrote:
>
> Hello everyone,
>
> I would like to find a single common threshold for multiple statistical images (one sample t test, output from randomise) when correcting for multiple comparisons. I would be happy to hear your opinion on how to do it best. At the moment I am considering two options, but maybe there are better ones.
>
> 1) FDR
> Is it possible for the FSl fdr command to find a threshold when the nifti image contains several volumes (concatenated *vox_p_tstat* maps from randomise)? When testing, it works, but I would like to confirm that the threshold I receive is indeed computed using all p values from several volumes in the nifti.
>
> Would it also make sense to use uncorrected TFCE image (*_tfce_p_tstat*) to preserve some spatial contingency among voxels?
>
> 2) TFCE and max value across images
> I was wondering whether one could modify the randomise command such that TFCE p values are corrected based on the maximum TFCE value across all voxels and all images in each permutation providing a common distribution of max values for all images?
>
> Many thanks in advance!!
> Best, Blazej
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