PowerPoint Presentation - Group Analysis with AFNI Programs

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Null Hypothesis:

H0 : m1 = m2 = É = mr

i.e., subject type has no effect on mean signal in this voxel

Alternative Hypothesis:

Ha : not all mi are equal

i.e., at least one subject type had a different mean FMRI signal

Ą3dANOVA is effectively a generalization of the unpaired t-test to multiple columns of data (a further refinement will be introduced with 3dANOVA3)

ĄAs such, 3dANOVA is probably not appropriate when comparing results of different tasks on the same subjects (need a generalization of the paired t-test: 3dANOVA2)

ĄDifference from doing unpaired t-tests on pairs of columns: variance estimates are all pooled together, increasing the denominatorial degrees of freedom

ĄAssumption is that data fluctuations in each column have same variance

Y2,n2

Yr,nr

Y1,n1

Yr,2

Y2,2

Y1,2

Yr,1

Y2,1

Y1,1

Measurements

(e.g., percent signal change)

Factor levels (e.g., subject types)

Data from Voxel V

e.g., Subjects

are multiple

measurements

within each level