You would do the long analysis using a random effects analysis. For each 
subject you can get a slope (this won't work if the subject only has 1 
time point), then concatenate the slopes into a file and run mri_glmfit, 
then follow the procedures from the archive email you reference.
doug

On 02/24/2015 08:35 PM, Janosch Linkersdörfer wrote:
> Hi Doug and others,
>
> I would like apply (Monte Carlo simulation) cluster correction (as opposed to 
> the implemented vertex-wise FDR correction) on the results from a 
> longitudinal study I analyzed using the LME toolbox. The design is unbalanced 
> (different number of time points, from 1 to 4, per subject).
>
> In this thread 
> (http://www.mail-archive.com/freesurfer%40nmr.mgh.harvard.edu/msg35367.html) 
> you, Doug, suggested, if I understand correctly:
>
> - concatenating the images using `mris_preproc --paired-diff`
> - smooth with the same kernel size as used in the lme analysis
> - running `mri_glmfit` on them with an fsgd file that uses the same 
> covariates and the same contrast (excluding the interaction term with time) 
> as used in the lme analysis
> - overwriting sig.mgh with the one from the lme analysis
> - running `mri_glmfit-sim --cache`
>
> How would I extend this to my case where I don't have pairwise images, but 1 
> image for some participants, for others up to 4?
>
> Thanks a lot,
>
> Janosch
>
>
>
>

-- 
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu
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Fax: 617-726-7422

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