Dear SPM-experts,
I have a question regarding an experimental task. We have 2 groups of subjects (different age) scanned at 2 separate occasions one month apart with 2 different sleep conditions before the scanning. In the fMRI task, we have some conditions with 1 specific contrasts of interest. In the beginning of data collection we changed the scanner sequence and the number of slices and therefore, some of the subjects have different number (45 or 46) of slices on their 2 scanning sessions. This, I believe, makes it impossible to model both sessions together at 1:st level.
I made separate 1:st level models for the 2 sessions with corresponding contrasts of interest. Now I want to perform 2:nd level analyses and this is where I come in to trouble.
First of all I want to see the overall effect of the task conditions. The obvious way would to perform a one sample t test with contrasts from first level. However, since I have 2 contrasts for each subject (from 2 separate sessions) I guess I cannot put all the 1:st level contrasts in to one test, because the contrasts are not independent (since every subject has 2 contrasts). Is there a simple way to handle this? (i.e. modelling the subjects in a reasonable way).
Secondly, I am interested in both effects of the sleep conditions (i.e. between sessions), the effect of age group, as well as interaction between age and sleep condition. The effect of sleep is easy (paired t tests), as well as the interaction (I used a flexible factorial design), but I read in earlier emails that it is not valid to test for group differences in the flexible factorial. Is this true? If yes, is there another way?
Best regards
Sandra
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