Dear Anderson,

Thank you very much for your reply. Using just one F-test indeed seems to make a lot more sense.

To come back to your suggestion to add three t-contrast with opposing sign, I guess my design matrix could look like this (when testing a 2x2 ANOVA having 2 factors with 2 levels):

		Ax	Ay	Bx	By	F1
C1	A>B	1	1	-1	-1	X
C2	B>A	-1	-1	1	1	X
C3	X>Y	1	-1	1	-1	X
C4	Y>X	-1	1	-1	1	X
C5	interaction+ve	1	-1	-1	1	X
C6	interaction-ve	-1	1	1	-1	X

Do you think this design matrix looks as it should? Or am I misunderstanding something?

Yet again, thanks a lot for your help!

Kind regards,

Maya

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From: FSL - FMRIB's Software Library [[log in to unmask]] on behalf of Anderson M. Winkler [[log in to unmask]]

Sent: Thursday, January 24, 2013 2:05 PM

To: [log in to unmask]
Subject: Re: [FSL] 2x2 ANOVA randomise

Dear Maya,

Your F-tests are correct but perhaps they are not very useful. If you'd like to look at both tails, you may consider additional t-tests with the opposite sign to those you already have. If you'd like an F-test over all the three t-contrasts, then in the Glm GUI, define something as:

		EV1	EV2	EV3	EV4	F1
C1	A	1	0	0	0	x
C2	B	0	1	0	0	x
C3	AB	0	0	1	0	x

About the F=15 being not significant, it's actually not so high (consider a t of ~3.8). Plus, here it's non-parametric, so the significances aren't identical to what would be expected from the F distribution (which also depends on the number of df, which I think you didn't mention).

All the best,

Anderson

2013/1/24 Schutte, J.L. (Maya) <[log in to unmask]>

Dear Anderson,

Thank you very much for your help.

I run the analysis as you said, including the ' -f design.fts', but still have a question concerning the results and was wondering if you could give some advice on this.

The t-test for contrast 2 shows a large significant result, however this does not show up in the f-test of contrast 2. Also, the uncorrected f-stat image of C2 shows a maximum f-value of approximately 15, by which I would expect some clusters to survive the corrected threshold. Do you have any idea what causes this discrepancy?

Many thanks in advance!

Kind regards,

Maya

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From: FSL - FMRIB's Software Library [[log in to unmask]] on behalf of Anderson M. Winkler [[log in to unmask]]
Sent: Tuesday, January 22, 2013 5:15 PM
To: [log in to unmask]
Subject: Re: [FSL] 2x2 ANOVA randomise

Dear Maya,

Use the second (with the "-f design,fts"). The first will run only the t-tests (the contrasts C1 to C3).

In case you are interested only on the F-test, and want to skip the t-tests to save time, include the option --fonly, but still keep the "-t design.con" there.

All the best,

Anderson

2013/1/22 Schutte, J.L. (Maya) <[log in to unmask]>

Dear FSL mailinglist,

I am analyzing DTI data and would like to use a 2x2 ANOVA having two factors with 2 levels. When using the FEAT manual, my design matrix would look like this:

		EV1	EV2	EV3	EV4	F1	F2	F3
C1	A	1	0	0	0	x
C2	B	0	1	0	0		x
C3	AB	0	0	1	0			x

However, when using the randomise function I am not entirely sure about the input arguments -t and -f. Should I include the -f design.fts in the commandline because I included 3 f-test in my design matrix, or is including the -t design.con sufficient?

In other words, which of the command below should I use, and why?

randomise -i all_FA_skeletonised -o tbss -m mean_FA_skeleton -d design.mat -t design.con -n 5000 --T2 -V

or

randomise -i all_FA_skeletonised -o tbss -m mean_FA_skeleton -d design.mat -t design.con -f design.fts -n 5000 --T2 -V

Thanks a lot in advance for any suggestions.

Kind regards,

Maya Schutte