Hi,
I have a an experimental situation that consist of three stimuli with
increasing intensity. I have two groups. I wouldn't like to model
reciprocity and linear trends in both activations and deactivations. I
wonder if this seem correct, and this is how I did it:
FIRST-LEVEL (S1-3=stimuli with intensity 1-3)
COPE 1: S1 1_0_0
COPE 2: S2 0_1_0
COPE 3: S3 0_0_1
COPE 4: Positive linear effect -1_0_1
COPE 5: Negative linear effect 1_0_-1
I then model the each group seperately. I feed COPE 4 and 5 in/up to the
second-level analysis to model both activation and deactivation where there
is a linear effect:
COPE 1: G1 +lin act 1_0
COPE 2: G1 +lin deact -1_0
COPE 3: G1 -lin act 0_1
COPE 4: G1 -lin deact 0_-1
COPE 5: G2 +lin act 1_0
COPE 6: G2 +lin deact -1_0
COPE 7: G2 -lin act 0_1
COPE 8: G2 -lin deact 0_-1
Now, if I assumed that the deactivation was greater the smaller the
activation or the other way around (inverse trends), how would that matrix
look? Suggestion: I then feed COPEs from the second level analyses in/up to
a third level analysis:
[COPE 2_3]COPE 1: G1 1_-1
[COPE 1_4]COPE 2: G1 -1_1
[COPE 6_7]COPE 3: G2 1_-1
[COPE 5_8]COPE 4: G2 -1_1
or that the amount of deactivation was "balanced" with that of activation...
[COPE 2_3]COPE 5: G1 1_1
[COPE 1_4]COPE 6: G1 1_1
[COPE 6_7]COPE 7: G2 1_1
[COPE 5_8]COPE 8: G2 1_1
I then investigate group differences at the fourth level:
[COPE 1_3=G1_G2]COPE 1: 1_-1
[COPE 1_3=G1_G2]COPE 2: -1_1
[COPE 2_4=G1_G2]COPE 3: 1_-1
[COPE 2_4=G1_G2]COPE 4: -1_1
[COPE 5_7=G1_G2]COPE 1: 1_-1
[COPE 5_7=G1_G2]COPE 2: -1_1
[COPE 6_8=G1_G2]COPE 3: 1_-1
[COPE 6_8=G1_G2]COPE 4: -1_1
Does this seem right? Thanks.
Kind regards,
Benny Liberg
|