Hi, Tom
Thank you for your fast reply. They are definitely helpful.
 
Best
 
Longchuan 
----- Original Message -----
From: [log in to unmask] href="mailto:[log in to unmask]">Thomas Nichols
To: [log in to unmask] href="mailto:[log in to unmask]">[log in to unmask]
Sent: Wednesday, July 23, 2008 2:24 PM
Subject: Re: [FSL] control gender effects from TBSS randomise (three groups)

Hi,

group  subjects  EV1 EV2 EV3 EV4

1            1            1      0        0       1
1            2            1      0        0       0
1            3            1      0        0       0
2            4            0      1        0       1
2            5            0      1        0       0
2            6            0      1        0       0
3            7            0      0        1       1
3            8            0      0        1       0
3            9            0      0        1       0


my t-test and F-test contrasts are like this:

C1     A-B         1   -1   0  0
C2     A-C         1    0   -1 0
C3     B-C         0    -1   1 0

OK, good.
 
C4     A-Sex      1    0    0 -1
C5     B-Sex      0    1    0 -1
C6     C-Sex      0    0    1 -1

These are junk... they don't make any sense.  The gender effect is in the model, and hence all inferences are controlled for gender (i.e. any additive gender effects are set aside).


C7       A            1    0    0  0  F1
C8       B            0    1    0  0  F2
C9       C            0    0    1  0  F3

C10   Sex       0   0   0  1 F4

These are fine.
 
So, my questions are:
1) if the design matrix and contrasts are correctly set up
 
See above.

2) Which results reflect the differences among the three groups after having gender effects controlled?

All inferences are controlled for gender.
 
3) Thomas mentioned that I can think about centering the gender variable with group if I have lots of data. I do have around 80 subjects and I would really appreciate if you would give me more specific information about this.

If you would like to control for a group-specific gender effect, you need to fit a group-by-gender interaction.  This entails splitting the gender EV into three groups *and* ensuring that the gender EV *within* each group are centered.

For example, using the gender EV you gave above, this would be
 2/3     0       0
-1/3     0       0
-1/3     0       0
  0     2/3      0
  0    -1/3      0
  0    -1/3      0
  0      0      2/3
  0      0     -1/3
  0      0     -1/3

Hope this helps.

-Tom
 
____________________________________________
Thomas Nichols, PhD
Director, Modelling & Genetics
GlaxoSmithKline Clinical Imaging Centre

Senior Research Fellow
Oxford University FMRIB Centre