Dear Jungwoo,
You definitely can, have a look at spm_ancova too:
https://github.com/spm/spm12/blob/master/spm_ancova.m
As Cyril describes, in an fMRI mass-univariate setting, there are a
number of things you have to take into account: high-pass filtering,
signal scaling, non-sphericity correction (temporal autocorrelation) and
multiple comparison correction (spatial smoothness). Once you have done
that, you basically rewrote (part of) SPM'94.
Best regards,
Guillaume.
On 27/05/2021 07:34, Jungwoo Kim wrote:
> Hello, SPM users!
>
> If I can specify every columns of design matrix, can I just use pinv function to get beta weights or residuals?
> In the case where I have my own elements in design matrix, it is burdensome to convert them into a form of matlabbatch.
>
> Actually, I checked the result myself, and found out that correlation of betas from each results were more than .95 but show some difference in their magnitude.
>
> So I thought it may due to some modification of the brain data itself, but I found no clue.
> Your answers would be of great help.
>
> Thank you!
>
> Best,
> Jungwoo Kim.
>
>
>
>
>
--
Guillaume Flandin, PhD
Wellcome Centre for Human Neuroimaging
UCL Queen Square Institute of Neurology
London WC1N 3BG
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