Print

Print
Hi,

Assuming you're using the -D option with randomise, this is fine.  One small point is that the interpretation of C1 is not the group mean, but the positive linear relationship between your dependent variable and Behav, adjusted for gender.  I'm guessing you were already aware of that, but figured I'd mention it anyhow.

Cheers,
Jeanette


On Wed, Jun 12, 2013 at 9:47 AM, Xiaoyun Li <[log in to unmask]> wrote:
Dear experts,

I am running the structral shape analysis with FIRST. In the study, I have one group and one psychometrical variable. I run the correlation analysis between the group means and the behavioural variable. However, the numbers of genders are unbalance. Therefore, I need to remove the confound of the gender effect from the multiple comparison. I would like to know if my Glm design matrix is correct. If not, what should I do? Thanks a lot.

Glm design matrix: (for example)

Evs:
Group    Ev1       Ev2
            Behav    Sex
1            36          1
1            28          2
1            27          2
1            15          1
1            12          1
1              8          1
1              0          2
1              3          1
1            40          1
1            34          1
1              5          1
1            14          2
1            17          1
1            29          1
1              7          2
1            13          1

Contrasts & F-tests:
Contrsts: 2              F-tests: 0

              Title               EV1          EV2
C1      group mean         1              0
C2      gender                 0              1