answers below


On 3/7/17 7:54 AM, 刘丽 wrote:

Dear FS Experts,

I have one group to compare the difference between their preoperative and postoperative after one month. I followed http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/LongitudinalTutorial to process data. I run these command in number 2. Longitudinal Image Processing

1. recon-all –s sub01_MR1 –all / recon-all –s sub01_MR2 –all

2. recon-all -base sub01 -tp sub01_MR1 -tp sub01_MR2 –all

3. recon-all -long sub01_MR1 sub01 –all / recon-all -long sub01_MR2 sub01 –all

I am confused about choosing which kind of analysis in the page http://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalStatistics And I tried http://surfer.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova

The “rmanova.fsgd”:

GroupDescriptorFile 1 

Class sub01

Class sub02

Variables                        TP1-vs-TP2

Input         sub01_MR1     sub01       1

Input         sub01_MR2     sub01       -1

Input         sub02_MR1     sub02       1

Input         sub02_MR2     sub02       -1

“tp1-va-tp2.mtx”:  0 0 … 1 

And I look in one mail in the list, say “one group to use Paird Analysis easier”.  http://surfer.nmr.mgh.harvard.edu/fswiki/PairedAnalysis

“pairs.fsgd”:

GroupDescriptorFile 1

Class Main 

Input         sub04_MR1     Main

Input         sub04_MR2     Main

Input         sub05_MR1     Main

Input         sub05_MR2     Main

“paird-diff.fsgd” :

GroupDescriptorFile 1

Class Main 

Variables Age

Input         sub04pair   Main 24

Input         sub05pair   Main 27

“mean.mtx”: 1 0

My question

1. Are the above several files I set up correct??There are inconsistent results in them… So which one should I choose??

Assuming you have no covariates, they should give identical results. Note that for the paired-diff, you need to subtract tp1 from tp2 manually and pass the result to mri_glmfit.

2. I found the increase or decrease a subjects had a great influence on the analysis result, how to filter the participants??

not sure what you mean hear. can you elaborate?

Looking forward to reply, and thanks very much!

Kind regards,

Livia 



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