For A-TP1-vs-B-TP1, you just create a contrast (not a variable in the
FSGD). The design matrix from your FSGD will have 6+4=10 regressors. The
contrast for A-TP1-vs-B-TP1 would then be
1 -1 0 0 0 0 0 0 0 0
This computes the difference between Class A-TP1 and B-TP1
On 7/13/2021 11:07 AM, Ritobrato Datta wrote:
External Email - Use Caution
Good morning Doug,
I am trying to create a contrast matrix (also attached as a text file)
for the following conditions -
I have two treatment arms A and B
For treatment arm A, I have subjects 1, 2, 3 imaged at TP1, TP2, TP3
For treatment arm B, I have subjects 4, 5, 6 imaged at TP1, TP2, TP3.
I have used the repeated measures ANOVA tutorial to set up some of the
contrasts as follows -
GroupDescriptorFile 1
Title A-Vs-B-Long
Class A-TP1
Class B-TP1
Class A-TP2
Class B-TP2
Class A-TP3
Class B-TP3
Variables A-TP1-vs-A-TP2 A-TP1-vs-A-TP3 B-TP1-vs-B-TP2
B-TP1-vs-B-TP3 A-TP1-vs-B-TP1 A-TP2-vs-B-TP2 A-TP3-vs-B-TP3
Input sub1-TP1 A-TP1 1 1 0 0
Input sub2-TP1 A-TP1 1 1 0 0
Input sub3-TP1 A-TP1 1 1 0 0
Input sub4-TP1 B-TP1 0 0 1 1
Input sub5-TP1 B-TP1 0 0 1 1
Input sub6-TP1 B-TP1 0 0 1 1
Input sub1-TP2 A-TP2 -1 0 0 0
Input sub2-TP2 A-TP2 -1 0 0 0
Input sub3-TP2 A-TP2 -1 0 0 0
Input sub4-TP2 B-TP2 0 0 -1 0
Input sub5-TP2 B-TP2 0 0 -1 0
Input sub6-TP2 B-TP2 0 0 -1 0
Input sub1-TP3 A-TP3 0 -1 0 0
Input sub2-TP3 A-TP3 0 -1 0 0
Input sub3-TP3 A-TP3 0 -1 0 0
Input sub4-TP3 B-TP3 0 0 0 -1
Input sub5-TP3 B-TP3 0 0 0 -1
Input sub6-TP3 B-TP3 0 0 0 -1
Question 1 - My question is how do I setup the contrasts for the
different treatment arms -
A-TP1-vs-B-TP1 A-TP2-vs-B-TP2 A-TP3-vs-B-TP3
Question 2 - Also I have age and cognitive scores for each timepoint.
How do I add those to the contrast file ?
Thank you for the help,
Regards
Rito
On Mon, Jul 12, 2021 at 10:51 AM Douglas N. Greve
<dgr...@mgh.harvard.edu <mailto:dgr...@mgh.harvard.edu>> wrote:
Yes, it will work on both. If you use a table, then pass the table
with --table tablefile instead of --y
On 7/12/2021 7:54 AM, Ritobrato Datta wrote:
External Email - Use Caution
Good morning,
Thanks Doug for the answers. Quick naive question. The analyses I
want to perform are on volumetric data parcellated using aseg and
not surface data.
Does mri_glmfit work with the output of the asegstats2table or on
voxelwise FA maps ?
Many thanks
Rito
On Fri, Jul 9, 2021 at 4:04 PM Douglas N. Greve
<dgr...@mgh.harvard.edu <mailto:dgr...@mgh.harvard.edu>> wrote:
On 7/9/2021 11:44 AM, Ritobrato Datta wrote:
External Email - Use Caution
Hi All,
I have the following data –
I have 205 subjects - each subject was imaged at 3
timepoints (baseline, followup 1 and followup 2)
The 205 subjects are split in two treatment arms with 100
subjects in the first one and 105 subjects in the second one.
For each timepoint, I have created FA maps in their native
diffusion space.
I have also extracted the mean FA maps for 187 ROIs using
mri_segstats.
For each timepoint, I have saved the results as a matrix (FA
in 187 ROIs x 205 subjects) in a text file.
So I have three files for the three timepoints.
I have the age and cognitive score for each subject at each
timepoint. And their gender.
I want to answer the following questions –
1. Do the baseline FA correlate with the corresponding
cognitive score at baseline ?
This is a straight forward group analysis, so see
*MailScanner has detected a possible fraud attempt from
"secure-web.cisco.com" claiming to be*
https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
<https://secure-web.cisco.com/1kTEkM43RMM06eViww_c18Pc-0P94xql3L2qK8iLarzzC3y3ZVsJIyVlzwF_FfFDswP_67I4PBLfYANWVTXuX-4X-dgKz6-k68o_AL_cvOJiFFFtpwIkd_pFO6m_tuaJtslVIIdmaO4umpQP9t8aMp-MPFEXKVDhKSsBgBNLINu7lLfDwLYKxiP2ZBbWcSlnNZ_KCTA3HDdKNI3PG_H6HTqTiwoC5vQjUicP6uxqYdn-HGl01ZnCt5V89LbOE3usywXIQtA_sZ4MgIcXGQDbj2g/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FFsgdExamples>
(maybe
the Two Groups (1 Factor, Two Levels), One Covariate
<https://secure-web.cisco.com/1Rg-kxMT-3fQYeRaisunO8_YESB0oLHn151lBD4p9GXp_k96wsb_0fS3wm9AsXst9uQO9dbqRePqf6ijMZUnk_-eFE6HtBGPMjtgURPbRAk_5EC3Q0F3VX-mhUssaYthkDfBZtL6yv0bGjJhKRQulYDXsfvmbpUWl4VH11l7cdQD2p1m_QzCr5liecQPY6UPX6OiGxGITQdALxOE9JdoIyXv0aJ_ozwU_Lw9H2pA2lcXdQEb4RTfOartXbc2P58SNR1mmH4DIzvfp7MxOG1oqRA/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FFsgdf2G1V>)
1. I am interested in testing whether the FA changed
significantly across the different timepoints and does
that relate to the change in the cognitive score
See *MailScanner has detected a possible fraud attempt from
"secure-web.cisco.com" claiming to be*
https://surfer.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova
<https://secure-web.cisco.com/1l3pHvz1wZceoR8e52Wja_MsMNej9vi7VZZmS8c-z4MS9JGbI3TYJJMikCYf0s7kjh03rhGqRoz4Nqw5FjnWspM8jPaxx5vhTf6cgH1nVEw8kZAyGg-kIVm5tQNWqRiQ-S-cYslSRjWA5zKzXqqcgwKeSWShLW2aw-XRuSrV9IBOmdGQq2pERdmOAqXTVIKchIwtjPqefKoRqoYe4OZ6h_wlLLnBEFs_BJGv4A9Eabyq07igMiO8NeE8VYMkEhQFl0KlX_VyWmlAm-N28VS8hcg/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FRepeatedMeasuresAnova>
1. Is there an effect of treatment on this change in FA
across time ?
Also see *MailScanner has detected a possible fraud attempt
from "secure-web.cisco.com" claiming to be*
https://surfer.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova
<https://secure-web.cisco.com/1l3pHvz1wZceoR8e52Wja_MsMNej9vi7VZZmS8c-z4MS9JGbI3TYJJMikCYf0s7kjh03rhGqRoz4Nqw5FjnWspM8jPaxx5vhTf6cgH1nVEw8kZAyGg-kIVm5tQNWqRiQ-S-cYslSRjWA5zKzXqqcgwKeSWShLW2aw-XRuSrV9IBOmdGQq2pERdmOAqXTVIKchIwtjPqefKoRqoYe4OZ6h_wlLLnBEFs_BJGv4A9Eabyq07igMiO8NeE8VYMkEhQFl0KlX_VyWmlAm-N28VS8hcg/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FRepeatedMeasuresAnova>
Can you please suggest what programs in freesurfer will
allow me to test these questions on both voxelwise and ROI
wise ?
Many thanks for your help and guidance,
Regards
Rito
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