External Email - Use Caution
| 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 |
| A-TP1-vs-B-TP1 | A-TP2-vs-B-TP2 | A-TP3-vs-B-TP3 |
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 <dgreve@mgh.harvard.edu> wrote:
On 7/9/2021 11:44 AM, Ritobrato Datta wrote:
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 (maybe the Two Groups (1 Factor, Two Levels), One Covariate)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 –
- Do the baseline FA correlate with the corresponding cognitive score at baseline ?
See MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be https://surfer.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova
- 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
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
- Is there an effect of treatment on this change in FA across time ?
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