Simply put your raw IQ scores into one column, demean as one, and drop the last column in your contrasts list. This will allow you to model the linear effect of IQ(?) on your expected signal... but spread the misfit across your signal in a unpredictable way if this is not the case.
--
Dave Flitney
IT Manager, FMRIB Centre
On 22 Nov 2011, at 17:37, Roger Jou <[log in to unmask]> wrote:
> Dear Prof Smith,
>
> Thank you for clarifying my error. I understand what this means conceptually,
> but could please show me what the design.con and design.mat looks like? I want
> to be certain I am on the right track. Thanks again.
>
> Regards,
>
> Roger
>
> Quoting Stephen Smith <[log in to unmask]>:
>
>> Hi - no this is incorrect - if you want to "control for" IQ this needs to be a single EV (across both groups) that will attempt to model out the effect of IQ.
>> However that will only succeed (ie remove this confound in the group difference) to the extent that the effect of IQ on the data is linear and additive - which cannot necessarily be assumed.
>> Cheers.
>>
>>
>> On 19 Sep 2011, at 19:42, Roger Jou wrote:
>>
>>> Dear FSL Experts,
>>>
>>> I am conducting a TBSS analysis on FA, MD, AD and RD and plan to use TFCE. The study consists of two groups (control = 11 and patient = 19) who differ significantly in IQ. Therefore, I wanted conduct the analysis controlling for IQ and would be extremely grateful for help in generating the appropriate design.con and design.mat files.
>>>
>>> I have looked through the forum for answers and have drafted the following:
>>>
>>> design.con
>>>
>>> /NumWaves 4
>>> /NumContrasts 2
>>> /PPheights 1 1
>>> /Matrix
>>> 1 -1 0 0
>>> -1 1 0 0
>>>
>>> Can you please tell me whether this design.con file is correct?
>>>
>>> design.mat
>>>
>>> /NumWaves 4
>>> /NumPoints 30
>>> /PPheights 86 86
>>> /Matrix
>>> 1 0 -8.4 0
>>> 1 0 12.6 0
>>> 1 0 16.6 0
>>> 1 0 0 0
>>> 1 0 2.6 0
>>> 1 0 -22.4 0
>>> 1 0 -1.4 0
>>> 1 0 8.6 0
>>> 1 0 -3.4 0
>>> 1 0 -4.4 0
>>> 1 0 -0.4 0
>>> 0 1 0 35.7
>>> 0 1 0 15.7
>>> 0 1 0 10.7
>>> 0 1 0 8.7
>>> 0 1 0 -5.3
>>> 0 1 0 -40.3
>>> 0 1 0 22.7
>>> 0 1 0 16.7
>>> 0 1 0 -11.3
>>> 0 1 0 -15.3
>>> 0 1 0 -13.3
>>> 0 1 0 -1.3
>>> 0 1 0 -6.3
>>> 0 1 0 8.7
>>> 0 1 0 1.7
>>> 0 1 0 29.7
>>> 0 1 0 -7.3
>>> 0 1 0 -50.3
>>> 0 1 0 0
>>>
>>> Can you please tell me whether this design.mat file is correct?
>>>
>>> Also, I wanted to double check that the PPheights are the difference between the most negative and most positive demeaned IQ for the entire sample, and the IQ needs to be demeaned separately for control and patient groups.
>>>
>>> Finally, in order to run this would the procedure the same as that indicated on the main TBSS documentation page, just using the above for the for the design.mat and design.con files below:
>>>
>>> randomise -i all_FA_skeletonised -o tbss -m mean_FA_skeleton_mask -d design.mat -t design.con -n 500 --T2 -V
>>>
>>> Thanks in advance for your help!
>>>
>>> Roger
>>>
>>
>>
>> ---------------------------------------------------------------------------
>> 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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