Hi all,
I've found similar topics but none answered my specific problem.
I've done a study in which I've scanned 12 subjects on 3 different days, and 2 scan sessions on each day.
So in total 6 scans per subject.
There are 3 baseline sessions, all followed by a 'challenge' scan where the subjects were under influence of a drug challenge or placebo challenge.
I started with doing paired t-tests on the baseline scans and their following challenge scan to see the effect of the drug or placebo on each separate day.
Now however, I want to compare these 'drug effects' to see if they are reliable in time (and different from placebo effect).
For this, I want to do a third level analysis: a t-test on the results of the paired t-tests.
(So, what is the drug effect of day 1 and how does this differ from the drug or placebo effect on day 2)
The problem is as follows:
I have some missing data sets in one of my tasks because of poor task performance.
I understand that this is not a problem with the paired or 'triple' t-test or in a repeated measures ANOVA because the EV's with the subjects means will correct for this.
But what if I use the cope files of the paired t-tests for the t-test to see differences in the drug effect between days?
Can I only use those subjects from which I have all scans, so those that were both in the paired t-test of day 1 and in the paired t-test of day 2?
And what if I would do a 2x2 ANOVA, with the four scans of 2 consecutive days and thus looking at pre/post challenge and day1/day2 with of course special interest in the interaction term?
Do I then need to include only the subjects from which all four scans are present or could I also include subjects with missing scans since you also define EVs with the subjects means and thus 'tell' the program which scans are missing?
How does FSL deal with the within-subject and between-subject variances in these cases?
Many thanks in advance for clarifying this!
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