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Hi Vincent,

Thanks for sending this careful evaluation. It's an impressive 
investigative work. However, you still didn't show the design.con file.

Thanks.

All the best,

Anderson


Am 12.03.14 21:05, schrieb Vincent Koppelmans:
> Hi Anderson,
>
> I ran a couple more analyses, 8 in total:
>
> (data demeaned yes/no) * (design.mat demeaned yes/no) * ( -D in 
> randomise yes/no)
>
> The dataset is very small (8 subjects) and thus, all permutations in 
> randomise were executed.
>
> I compared the resulting checksums of the tstat and p-value maps:
>
>
> (link to .svg: https://dl.dropboxusercontent.com/u/6747155/flowchart.svg )
>
> As you can see from the figure:
> - p-values were the same for all models with the -D option
> - p-values were the same for all models without the -D option
> - tstats were the same for all models with the unaltered data file
> - tstats were the same for all models with the manually demeaned file
>
> However, I would have expected for example OPTION 07 and OPTION 08 to 
> be similar because regardless of the -D option, both use demeaned data 
> as well as a demeaned matrix.
>
> Why is this not the case?
>
> Thanks,
>
> - Vincent
>
>
> Op 11 mrt. 2014, om 18:26 heeft Anderson M. Winkler 
> <[log in to unmask] <mailto:[log in to unmask]>> het volgende 
> geschreven:
>
>> Hi Vincent,
>>
>> Could you paste here the design.mat and the design.con files?
>> Another thing is which image are you using to compare the results? 
>> The comparison must use the images of the statistic, not of the 
>> p-values, because even with the same seed, there is a possibility, 
>> depending on the design, that the shufflings aren't exactly the same 
>> (except of course in the exhaustive case), then the p-vals may vary a 
>> bit.
>>
>> Thanks.
>>
>> All the best,
>>
>> Anderson
>>
>>
>> Am 11.03.14 21:22, schrieb Vincent:
>>> I have VBM data: 1 group with 1 continues covariate.
>>> I am interested in the association between the covariate and local 
>>> gray matter volume.
>>>
>>> From what I understand from Jeanette Mumford's website 
>>> (http://mumford.fmripower.org/mean_centering/), I do not need to 
>>> mean center the covariate, and according to the FSL GLM wiki 
>>> (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Single-Group_Average_with_Additional_Covariate) 
>>> I should use the -D option.
>>>
>>> If I understand correctly the -D option demeans both the design 
>>> matrix as well as the data (FSL v 5.0 and later). To get a better 
>>> understanding about what -D is exactly doing, I ran randomise two times:
>>>
>>> 1) On a regular 4D nifti image with smoothed gray matter images in 
>>> MNI space:
>>> randomise \
>>> -i 4D_GM.nii.gz \
>>> -o vbm \
>>> -d design.mat \
>>> -t design.con \
>>> -m ../mask.nii.gz \
>>> -n 500 \
>>> -T \
>>> -1 \
>>> -D
>>>
>>>
>>> 2) On the same 4D nifti file that I manually demeaned:
>>>
>>>    fslmaths 4D_GM.nii.gz -Tmean mean.nii.gz
>>>    fslsplit 4D_GM.nii.gz
>>>    for i in `ls vol*`; do fslmaths ${i} -sub mean.nii.gz new_${i}; done
>>>    fslmerge -t 4D_GM_demeaned.nii.gz new*
>>>
>>> with a manually demeaned covariate in the design matrix
>>>
>>> other files were kept constant (design.con, mask.nii.gz)
>>>
>>> randomise \
>>> -i 4D_GM_demeaned.nii.gz \
>>> -o vbm \
>>> -d design.mat \
>>> -t design.con \
>>> -m ../mask.nii.gz \
>>> -n 500 \
>>> -T \
>>> -1
>>>
>>>
>>> The results from these two methods were not the same.
>>> When I subsequently added the -D flag to the second run with the 
>>> manually demeanded data, the results were the same as with those of 
>>> the 1st model.
>>>
>>> Could anybody please explain the discrepancy between the results of 
>>> 1) and 2)?
>>>
>>> - Vincent
>