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Dear Matthew,

this seems to have worked but you managed to confuse me a little more with regards to the F-test. Sorry. :-) You say ("e.g. -F 2.3"). I thought that if I only specified one F-test in my design and checked the three boxes, this would be a combined F-test. If what you are writing is correct in my case, then should I write  -F 1.2.3 in order to get the full F? Sorry, I don't understand the "2.3"....

Another quick question:

Can I combine the F-test with the --T2 option or are these exclusive? I am not sure I quite understand whether these two options can be run together in one analysis or whether they should be run separately.

Thanks so much for your help,

sven


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Hello Sven,
                   It looks like you are using a lower case ( -f ) for the
F-test cluster threshold option, this should be a
capital F ( e.g. -F 2.3 ) - can you try this and let us
know if the error changes?

Kind Regards

Matthew

> Dear FSLers,
>
> I am new to FSL and am currently analysing 4 groups DTI TBSS data and have
> worked my way through the tutorial and posts on the mailing list. However,
> I am still confused with the F-Test.
>
> If I include the -f design.fts option but not specify an -F [number]
> option, I get an error message that no specific option was selected but if
> I do say -F 1 then I get another error message. So concretely, I had used
> the example on the TBSS stats webpage:
>
> randomise -i all_FA_skeletonised -o tbss -m mean_FA_skeleton_mask -d
> model_test1.mat -t model_test1.con -f model_test1.fts -n 5000 -c 2 -V
>
> Message:
> Loading Data:
> Data loaded
> 1.16979e+44 permutations required for exhaustive test of f-test 1
> Doing 5000 random permutations
> Warning! No output options selected. Outputing raw tstat only
>
> I had then tried
>
> randomise options: -i all_FA_skeletonised -o tbss -m mean_FA_skeleton_mask
> -d model_test1.mat -t model_test1.con -f model_test1.fts -n 5000 -c 2 -f 1
> -V
>
> but got
> Loading Data: ERROR: Program failed
>
> An exception has been thrown
> Unable to open 1
>
> Exiting
>
> _______
>
> If my design matrix is such that
>                 F-TEST
> 1 -1  0  0   check
> 1  0 -1  0   check
> 1  0  0 -1   check
> ……
> …… set of remaining t-contrasts here without selection of F, e.g.,
> 0  0  1  -1  not checked
> … etc
>
> What option should I use in randomize to get the output for my F-test?
> Should I use a combination of these to specify the contrast or can I
> ignore the error and check this once the statistics have run?
>
>
> Many thanks in advance for any suggestions!
>
> Sven
>