Hy Dylan, 

the design matrix and exchange blocks look fine to me. Simply using  [ 1 2 3 4 1 2 3 4 ]  for exchange blocks should be fine. 

You may also want to test the opposite contrast of [ 0 0 0 -1]. Currently it seems that you are only testing one direction of difference. 

Not being able to reject the null hypothesis is a result. 

Andrew

Originally posted by dylan sutterlin:

Hi,

I have a repeated measure experiment (pre, post intervention), and I would like to test for changes induced by the intervention. When I test, even at near 0 treshold, I don't get any results. Hence I would like to validate my design matrix and exchange blocks (which I don't fully understand). Any suggestions welcome!

I have set up my files in alphanumerical order : 

aXXX01-pre.txt
aXXX02-pre.txt
aXXX03-pre.txt
bXXX01-post.txt
bXXX02-post.txt
bXXX03-post.txt
...

My design matrix is comprised of one column per subject, and a contrast column :

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

Contrast = [ 0, 0, 0, 1] / or [1, zeros(1, nsub)]; (tried both ways)

Exchange bloacks = [ 1 2 3 4 1 2 3 4 ]
This is the part where I am not sure what it does!
I have tried, like in some exmples, to specify it as [1;2;3;4;1;2;3;4], and as reshape(repmat(1:nsub, 1, 2), 1, []);
In the last two cases, I get 'exchange blocks : no' in the output.

In all cases, even at very low T, I get no results. Thanks for letting me know if I did it the right way (and that there is no results in these data).

Great thanks,

Dylan