Hi,
This looks fine to me now that you are using copes and not the -D option.
All the best,
Mark
On 14 Mar 2014, at 09:38, Stefania Evangelisti <[log in to unmask]> wrote:
> Dear Mark,
> thank you very much for your quick feedback.
>
> In the meantime, I went on reading and studying,
> and eventually decided to perform a 1-sample ttest for each group, to get the mean effect whithin the group, with, for example, the command
>
> randomise -i 1sample_seed1_pz.nii.gz -o 1sample_Ttest_seed1_pz -1 -v 2.5 -T
>
> In 1sample_seed1_pz.nii.gz i concatenated the cope images for all patients obtained from level 2 of the analysis,
> and I decided to perform variance smoothin considering the small groups.
>
> And then perform the 2-sample ttest to compare the groups with the command
>
> randomise -i 2sample_seed1.nii.gz -o 2sampleTtest_seed1.nii.gz -d design.mat -t design.con -n 5000 -T -v 2.5
>
> In 2sample_seed1.nii.gz i concatenated the cope images for patients followed by the cope images for controls,
> and design.con now is the following:
>
> /ContrastName1 group A > group B
> /ContrastName2 group B > group A
>
> /NumWaves 2
> /NumContrasts 2
> /PPheights 1.000000e+00 1.000000e+0
> /RequiredEffect 2.801 2.801
>
> /Matrix
> 1.000000e+00 -1.000000e+00
> -1.000000e+00 1.000000e+00
>
> Hope this makes sense.
> Thank you all,
>
> Stefania
>
>
> ________________________________________
> Da: FSL - FMRIB's Software Library [[log in to unmask]] per conto di Mark Jenkinson [[log in to unmask]]
> Inviato: venerd́ 14 marzo 2014 9.50
> A: [log in to unmask]
> Oggetto: Re: [FSL] randomise resting-state data
>
> Hi,
>
> That generally looks fine, except that you should feed the COPE images into fslmerge and randomise, not the zstats.
> Also, you should not use -D in the randomise call, as you are interested in the mean values, so you certainly don't want to demean the data!
>
> All the best,
> Mark
>
>
> On 13 Mar 2014, at 14:14, Stefania Evangelisti <[log in to unmask]> wrote:
>
>> Dear fsl experts,
>> I'm quite new here
>> and I'm writing to ask you an opinion about the following analysis:
>>
>> resting state data, 9 patients and 9 healthy controls,
>> each subject has got 2 runs.
>> Following http://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/feat2/index.html#multisession I ran level 1 (seed-based functional connectivity for each run) and level 2 (mean across each subject's runs) on my data.
>> As for level 3, instead of the cluster thresholding that can be set from the Feat GUI, I'd like use randomise on these data to perform a 2-sample unpaired T-test to investigate differences in connectivity between the two groups.
>>
>> The steps that I'd do are the following:
>>
>> - concatenate (with fslmerge) in a 4D image (4Dimage_ztats) the zstat images of each subject (obtained in the 2nd level of the analysis)
>>
>> - use the following design.mat:
>> /NumWaves 2
>> /NumPoints 18
>> /PPheights 1.000000e+00 1.000000e+00
>>
>> /Matrix
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 1.000000e+00 0.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>> 0.000000e+00 1.000000e+00
>>
>> and the following design.con
>>
>> /ContrastName1 group A > group B
>> /ContrastName2 group B > group A
>> /ContrastName3 group A mean
>> /ContrastName4 group B mean
>> /NumWaves 2
>> /NumContrasts 4
>> /PPheights 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
>> /RequiredEffect 2.801 2.801 1.981 1.981
>>
>> /Matrix
>> 1.000000e+00 -1.000000e+00
>> -1.000000e+00 1.000000e+00
>> 1.000000e+00 0.000000e+00
>> 0.000000e+00 1.000000e+00
>>
>>
>> - run the following command:
>>
>> randomise -i 4Dimage_ztats -o ttest_randomise -d design.mat - t design.con -n 5000 -D -T
>>
>>
>> Am I making any conceptual mistake due to my inexperience?
>> Thank you very much for any suggestion.
>>
>> Stefania
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