Dear SPM experts,
I have a issue with setting up a 2nd level model for fMRI experiment. My apologies if my problem was already discussed elsewhere.
In short, I have 18 subjects for which multiple sessions were required. Unfortunately, the number of repeated measurements differs between the subjects (varies from 1 to 5 sessions).
I considered the following:
1. Modelling the subject factor by adding all sessions of the same subject in one first level analysis. A potential drawback comes up when I go on
with the second level analysis. Each contrast map from the first level analysis would be taken into account in equal measure, no matter the
number of repeated measurs for each subject.
2. I performed a first level analysis for each session and took all contrast maps into the second level. Additionally, I defined a multiple covariate
including a binary regressor for each subject with at least 1 session. The regressors assign the contrast maps to the respective subject. You
find the desgin matrix in the attachment.
My question: What is the best way to model the repeated measures? Is my second approach (admittedly a very easy one) appropriate to handle my problem?
Thank you in advance.
best,
Laurens
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