Thanks Doug. After using stage#1 of the longitudinal 2-stage model to create cross-sectional measuers of e.g. thickness change from tp1 to tp2 (e.g. thickness-pc1), I then did analyses in QDEC on these measures to see where in the brain such changes are

different from zero (within each group); and
different between groups (for every pair of groups in the current qdec table, e.g. F vs P)

For thickness-pc1 it all went fine, but for area-pc1 analyses, I get this error right after starting the MonteCarlo Null-Z correction: "Completed loading of analyzed data. fwhm.dat: 8.654965, rounded to 9. ERROR: CSDread(): could not open /usr/local/freesurfer/average/mult-comp-cor/fsaverage/rh/cortex/fwhm9/abs/th13/mc-z.csd". This happens regardless of the threshold used (e.g. 0.01 or 0.05)
In case it's relevant, for the thickness analyses (whose correction worked fine), the fwhm.dat was "10.190419, rounded to 11". I am using FS 5.3.0 (Ubuntu).

Thanks!
Tudor

On 17 June 2014 09:29, Douglas Greve <greve@nmr.mgh.harvard.edu> wrote:

It only needs to be accounted for when you compare across all 3 groups, in which case you'd have to use mri_glmfit
doug
On 6/17/14 12:07 AM, Tudor Popescu wrote:
Hi Doug,

Thanks... Presumably I'd just leave each possible pair of groups at a time in the qdec table, and delete rows corresponding to subjects of the remaining group? And then do stats on, e.g. "long.thickness-rate" to compare rate of change between the current pair of groups?
Doesn't variability across all 3 groups somehow have to be accounted for?

Tudor
On 16 June 2014 20:38, Douglas Greve <greve@nmr.mgh.harvard.edu> wrote:
Yes, you could do each separately.
doug

On 6/16/14 8:10 PM, Tudor Popescu wrote:
Dear FS list,

I have a data set with 3 groups (2 treatments, 1 control), each with equally-spaced time-points (pre and post structural scan). I've done the 3 longitudinal pre-processing steps, and stage#1 of the two-stage model, and I would prefer to run stage#2 (cross-sectional analysis of the difference) with QDEC as opposed to with mri_glmfit.

I know that QDEC is meant for 2 groups, but I see that designs with 4 or 6 groups can be analysed with QDEC (as per this FSGD examples page) whereas designs with 3 groups cannot be. It seems to me that an even number of groups is QDEC-able while an odd number isn't, but is there any workaround so that I can still use QDEC? Perhaps if I only do pairwise comparisons one at a time, i.e. treatment1 vs control and treatment2 vs control?

Many thanks!

Tudor
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