Print

Print


Hi Nancy Li,

To do a statistical comparison of the two groups, in the unpaired 2-sample t-test, the contrasts are [1 -1] and [-1 1].

To have the overall mean (across both groups), then use [1 1] for positive and [-1 -1] for negative.

All the best,

Anderson


On 19 January 2017 at 14:21, Nancy Li <[log in to unmask]> wrote:
Hi Anderson,
 
I want to make it clear, if there are two groups, we want to compare the mean activation of two groups. Just said before we should add (1,0) and (0 1) to the dsign.con. But if we want to get the whole mean activaion(two groups together),  we should add (1 1) and (-1 -1) to the design.con, is it right? Thank you so much for further confirmation.
 
Best
 
Nancy 





在 2017-01-19 18:15:11,"Anderson M. Winkler" <[log in to unmask]> 写道:
Hi Nancy,

Please see below:


On 18 January 2017 at 14:06, Nancy Li <[log in to unmask]> wrote:
Hi Anderson,
 
Great, It is what I want to know. So in the randomise command It seemed like this way:"

randomise -i   4D image  -o rando   -d design.mat -t design.con -n 5000 -T , design.con may be: 1   0

                                                                                                                                                                           0  1

                                                                                                                                                                           1  -1

                                                                                                                                                                                     -1  1


Is it right?


Yes, contrasts are fine. For the overall mean activation, however, you need to add two contrasts more: [1 1] and [-1 -1]. In randomise, you'd test these latter two by adding the option -1, that does sign-flippings.

 
And How about one sample ttest, it also the way to get the mean activation, but how to understand "There should be no repeated measures, i.e., there should only be one image per subjec ", It equals one subject only have one volume?  Need your help to confirmation. Thank you so so much!

Yes, one volume per subject.

All the best,

Anderson

 
 
Best
 
Nancy


At 2017-01-18 17:26:21, "Anderson M. Winkler" <[log in to unmask]> wrote:
Hi Nancy,

For the mean activation, using the same design shown in the Wiki, create a contrast that is [1 1].

All the best,

Anderson


On 17 January 2017 at 14:45, Nancy Li <[log in to unmask]> wrote:
Hi Anderson,
 
Thank you so much for sincere reply. Could you help me make sure if I want to get the mean activation of two different group, It could be done through one sample ttest(seperate group) or unpaired two group ttest, the results are same, is it right? Looking forward to more instruction. Thanks  a lot!
 
Best
 
Nancy




 

At 2017-01-16 18:26:55, "Anderson M. Winkler" <[log in to unmask]> wrote:
Hi Nancy Li,

An example of a two-sample t-test is in the manual, please see here: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Two-Group_Difference_.28Two-Sample_Unpaired_T-Test.29

All the best,

Anderson


On 13 January 2017 at 18:29, Nancy Li <[log in to unmask]> wrote:
Hi Colin Hawco,
Great thanks. It is more clear. We could also get the result of mean activation in two group contrast by design matris(1 0; 0 1; 1 -1; -1 1).  In my opinion  it is same to the result of  seperate one sample test, is it right? Looking forward to your confirmation. Thanks  a lot!
Best
Nancy
 

 







At 2017-01-14 01:43:04, "Colin Hawco" <[log in to unmask]> wrote:

Ahh I see. The means of permuting is different. Instead of randomizing group assignments, half the data is sign flipped (i.e. multiplied by -1). In this case, the data should follow a distribution centered around zero.

 

Everything in that wiki vis a vis the estimatablility of the true p-value remains true.

 

If you can possibly run 5000 permutations you should do so. if for no other reason than to please reviewer. I would recommend a minimum of 1000 or 2000 permutations.

 

 

Colin Hawco, PhD

Neuranalysis Consulting

Neuroimaging analysis and consultation

www.neuranalysis.com

[log in to unmask]

 

 

 

From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On Behalf Of Nancy Li
Sent: January-13-17 11:31 AM
To: [log in to unmask]
Subject: Re: [FSL] Question about randomise of one sample ttest

 

Hi  Colin Hawco,

 

Thank you so much. It may be understood easily if there is two group test. But in one sample test we want to get the mean activation, there is no permutation. How to undrestand the impact of different number of permutation. looking forward to your further help.

Best

 

Nancy

 

 





 

At 2017-01-14 00:19:51, "Colin Hawco" <[log in to unmask]> wrote:

more permutations give you a more accurate estimation of true significance. It also defines the possible increments and confidence limits of the calculated p-value, with more permutations providing greater confidence.

 

see:

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Randomise/Theory

 

 

Good luck,

 

Colin Hawco, PhD

Neuranalysis Consulting

Neuroimaging analysis and consultation

www.neuranalysis.com

[log in to unmask]

 

 

 

From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On Behalf Of Nancy Li
Sent: January-13-17 11:03 AM
To: [log in to unmask]
Subject: [FSL] Question about randomise of one sample ttest

 

Helo experts and folks,

 

I want to get results of mean group activation using randomise of one sample. The default permutation is 5000 in the command. My question is "is there difference between 500 and 5000 permuttaion of one sample test and why?" Looking forward to your help or may suggest some paper about this question. Thanks a lot in advance.

 

Best

 

Nancy