Hi,
I have some questions about the design matrix while conducting randomize modelling for my analysis.
I'm working on data of multiple sessions for each subject and thus need to perform multiple levels of modelling/analysis. My questions are specifically about the second level modelling that collapses over sessions within each participant (i.e., level 2: between-session analysis).
Level 1: Within-session analysis
Level 2: Between-session analysis
I have already done level 1 analysis (within-session analysis), which exhausts all the contrasts of interest.
As I proceed to the level 2 analysis (between-session analysis), I have some questions about the design matrix and I would like to use datasets from 3 subjects as examples for elaborations.
My inputs are lower-level FEAT directories: 6 inputs (3 subjects x 2 sessions per subject). The order of the inputs are as below.
subj1_session1
subj1_session2
subj2_session1
subj2_session2
subj3_session1
subj3_session2
In the EVs of full model setup, I have assigned each subject different group IDs as shown below based on the order of the inputs. (My understanding is that randomization would thus occur within each group but not across different groups. This setting would be different if we choose fixed effects modelling or mixed effects modelling: FLAME 1)
1
1
2
2
3
3
I have also specified 3 EVs, each representing each subject. The design matrix for the the 3 EVs is as below. This aims to collapse over sessions within each subject.
1 0 0
1 0 0
0 1 0
0 1 0
0 0 1
0 0 1
As for the Contrasts & F-tests, I have specified 3 contrasts, the same number as the subject number. The design matrix for Contrasts & F-tests is as below.
1 0 0
0 1 0
0 0 1
I was wondering if the setup above is correct for performing randomize modelling before I proceed to a higher level modelling later on (i.e., Level 3: Between-subject analysis).
Thanks so much!
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