I would use the following approach:
(1) Model each run separately - using different sessions - but in a single GLM.
(2) For group level modeling; I would use contrasts that are weighted
based on the number of trials in each run, this would produce 1 value
for each subject per task. If run 1 has 20 trials, and run 3 has 10
trials, the contrast would be: 20/30 0/30 10/30 for the three runs.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Sun, Apr 15, 2012 at 3:32 AM, Catherine Cho
<[log in to unmask]> wrote:
> My design is quite complicated - I need to analyze a 2 x 2 x 2 design (all independent variables)
> but I don't have enough number of trials to have SOA for each condition.
> Some conditions are missing a SOA for each run and some have only one value - what would be the best way to approach this issue?
> I'm wondering if I should combine all three runs, or do ANOVA with beta values later on.
>
> Thanks,
> Catherine
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