¥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