Hi, this is valid, and gives "valid" p-values out, but if you only
have 1 subject in one of the groups then the max number of possible
different permutations is the number of subjects in the other group,
which will limit how small the p-values can be, output by randomise.
Cheers, Steve.
On 13 Sep 2006, at 15:42, Andrea Cherubini wrote:
> We are analysing FA data of a single case patient to localise brain
> changes possibly related to a rare neurological dysfunction. We
> would like
> to do this using the TBSS and Randomise tools in FSL. Is it correct to
> design a two sample t-test (as with the script design_ttest2)
> considering
> the single patient as a group? If yes, how can we interpret the
> results of
> Randomise? Thanks for your help!
> Andrea
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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director, Oxford University FMRIB Centre
FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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