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¥2-Way ANOVA: test
for effects of two independent factors on measurements
HThis is a fully
crossed analysis: all combinations of factor levels are measured
åIn particular, if one factor
is ÒsubjectÓ, then all subjects are tested in all levels of the other
factor
åProgram is limited to balanced
designs: Must have same number of measurements in each ÒcellÓ (combinations of
factor levels)
HExample: Stimulus
type for factor A and subject for factor B
åEach subject is a level
within factor B (1 measurement per cell)
åThis is a fixed effect
« random effect model = Òmixed
effectÓ model
HExample: Stimulus
type for factor A and drug treatment for factor B
åEach subject is an
independent measurement for both factors, all levels
åThis is a fixed effect
« fixed effect model
åIf you also want to treat
subject as a separate factor, need 3dANOVA3
HExample: Stimulus
type for factor A, stimulus day for factor B
åWith one fixed subject, for
a longitudinal study (e.g., training between scan days)
åThis also is a fixed
effect « fixed effect
model
åAgain, multiple subjects
could be treated as independent measurements in 3dANOVA2,
or as a third factor in 3dANOVA3
see next pages
for description
of fixed and
random effects