I see. Thank you Doug !
Now I used the command lines from the qdec output in the terminal and I
constructed the next contrasts using them as a starting point. Now the results
seem more reliable and I can perform the Monte-Carlo with 5000 iterations.
I'll verify them once again with LME.
Alex.
--osgm is for one-sample group mean which is the simplest design
possible. It is probably not appropriate for your design. If you have
different inputs and different labels then you will get different results
On 10/30/2014 03:08 PM, Alex Hanganu wrote:
> Hi Martin,
>
> could you please confirm
right ! I totally forgot about this !
Thank you Martin !
Sincerely,Alex
On Thursday, October 30, 2014 3:33 PM, Martin Reuter
wrote:
Hi Alex,
the QDEC output (text in the terminal) should have the command line that was
used to call the mri_glmfit command.
Best, Martin
Hi Alex,
the QDEC output (text in the terminal) should have the command line that
was used to call the mri_glmfit command.
Best, Martin
On 10/30/2014 03:08 PM, Alex Hanganu wrote:
Hi Martin,
could you please confirm whether the glm analysis was correctly
performed ?
the command line is:
Hi Martin,
could you please confirm whether the glm analysis was correctly performed ?
the command line is:mri_glmfit --glmdir DIR --y
lh.thickness-pc1.stack.fwhm15.mgh --label lh.fsaverage.cortex.label --fsgd
FSGD_FILE --C Contrast-010..0.mtx --surf fsaverage lh
I get results, but I when I do t
Hi Alex,
you are not looking at a "one sample group mean" (osgd) so don't pass
that flag. Your design is probably something like
1 A other_co_vars_to_regress_out
(these are column vectors).
so contrast in that case would be [ 0 1 0... ]
That should create all outputs. All of this is really cr
Hi Martin,
thanks for confirming. I duplicated the parameter and got good results in qdec.
I also tried to repeat the analysis with mri_glmfit but I can't manage to come
to an end.In order to analyse the correlation between pc1 and parameter 'A', it
seems that I have to construct an fsgd file, th
Hi Alex,
you have to duplicate the parameter (it is basically fixed across time).
If you put 0 for tp2, it will average the two values, which is not what
you want. Otherwise I think it is the correct approach.
Best, Martin
On 10/21/2014 04:31 PM, Alex Hanganu wrote:
Dear Martin,
thank you
Dear Martin,
thank you very much for your answer ! and thanks for all the details !- yes, we
have exactly 2 time points in all subjects and the parameter is a single number.
In qdec - it seems that qdec table has to include the parameter 'A' both at
time 1 and at time 2 in order for "long_qdec_ta
Hi Alex,
the parameter is a single number that happens to be measured at time 1
right, eg baseline age? Lets call that parameter 'A' for the discussion
below. Also you have exactly 2 time points in all subjects?
There is two alternatives:
1. Simple approach (2-stage-model): You compute the
Dear FreeSurfer Experts,
How could the longitudinal analysis be performed in order to show
whether a parameter at time 1 is predictive of changes in cortical
thickness over time ? and can thecorresponding regions be shown in
FreeSurfer ?
In a statistical analysis, as we see it, we must perfo
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