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Furthermore, the way you have set it up is a paired t-test.
Follow the unpaired t-test in the wiki.
Hope that helps.
Cheers,
Andreas

Von:  FSL - FMRIB's Software Library <[log in to unmask]> on behalf of Colin
Hawco <[log in to unmask]>
Antworten an:  FSL - FMRIB's Software Library <[log in to unmask]>
Datum:  Dienstag, 15. März 2016 17:48
An:  <[log in to unmask]>
Betreff:  Re: [FSL] design matrix for testing A=B vs A!=B

You are committing a statistically fallacy here, by trying to say A and B
are equal. You cannot demonstrate that with that contrast. If p < 0.05 we
reject the null hypothesis that A and B are EQUAL. If p > 0.05, all we can
say is that we are not certain that any difference between A and B is a true
population difference for our probability level.
 
You cannot really show two groups are equal based on a traditional t-test.
In fact that is very tricky to do. The best you can do with this approach is
show they are not STATISTICALLY different at a given threshold.
 
 
Colin Hawco, PhD
Neuranalysis Consulting
Neuroimaging analysis and consultation
www.neuranalysis.com <http://www.neuranalysis.com>
[log in to unmask]
 
 
 

From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On Behalf
Of Qasim Bukhari
Sent: March-15-16 12:30 PM
To: [log in to unmask]
Subject: [FSL] design matrix for testing A=B vs A!=B
 

Dear FSL experts

I was running a study, and just wanted to make sure that my design matrix is
correct

I want to test whether my group A is equal to group B or not(both having 8
subjects). Null hypothesis is that it is NOT equal, and I want to prove it
false. (that means if A and B are equal I m happy)

 

Should these be my mat. file

 1 1 0 0 0 0 0 0 0 
 1 0 1 0 0 0 0 0 0
 1 0 0 1 0 0 0 0 0
 1 0 0 0 1 0 0 0 0
 1 0 0 0 0 1 0 0 0
 1 0 0 0 0 0 1 0 0
 1 0 0 0 0 0 0 1 0
 1 0 0 0 0 0 0 0 1
-1 1 0 0 0 0 0 0 0 
-1 0 1 0 0 0 0 0 0
-1 0 0 1 0 0 0 0 0 
-1 0 0 0 1 0 0 0 0
-1 0 0 0 0 1 0 0 0 
-1 0 0 0 0 0 1 0 0
-1 0 0 0 0 0 0 1 0 
-1 0 0 0 0 0 0 0 1

 

and con file

 1 0 0 0 0 0 0 0 0

-1 0 0 0 0 0 0 0 0

 

Would the design matrices remain the same if I reverse my null hypothesis ?
That means to make the null hypothesis that both groups are same (optimal
result that we disprove it). What would be the change in the design matrix
then?

 

 

I think I m doing something wrong, if anyone can help in this, I ll be
grateful ?

 

Thanks and kind regards,

Qasim