Hi,
I am trying to do a
second level analysis with repeated measures per subject. The simplified version
is:
a group of
10 subjects, consisting of two subgroups of 5 subjects each, and 2
copes per subject (in reality I have 3 groups, 87 subjects and 7
copes).
Copes were generated
using a model with orthogonal regressors at first level.
I want to apply an
analysis with 2 repetitions per subjects (the two copes) and test whether
cope1 distinguishes the two subgroups of 5 subjects better than cope
2.
My design then is as
follows:
group
EV1
EV2
EV3
EV4 ...
EV12
subject 1, cope
1
1
1
0
1
0
0
subject 1, cope
2
1
0
1
1
0
0
subject 2, cope
1
1
1
0
0
1
0
subject 2, cope
2
1
0
1
0
1
0
......
subject 9, cope
1
1
-1
0
0
0
0
subject 9, cope
2
1
0
-1
0
0
0
subject 10, cope
1
1
-1
0
0
0
1
subjects 10, cope
2 1
0
-1
0
0
1
Contrasts:
1 0 0 0 0 0 0 0 0 0
0 0 : first 5 subjects > last 5 subjects for cope 1
0 1 0 0 0 0 0 0 0 0
0 0 : the same for cope 2
1 -1 0 0 0 0 0 0 0 0
0 0: is the difference between the two subgroups greater for cope 1 than for
cope 2?
etcetera
So far I am happy
with my design. But I need to include one covariate for age and one for
gender as well. The demeaned age EV (EV13) would be something
like:
12
12
-7
-7
...
-11
-11
6
6
To avoid rank
deficiency, I can remove EV12 (the EV of subject 10), but I am not sure whether
this is allowed.
The alternative I
can think of is to go to 3rd level with diffcopes (cope1-cope2) as inputs.
Perhaps someone has
and idea how to include these covariates at second level?
Thanks,
Serge.