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.
