Irfan Ahmed, PhD

MANOVA (multivariate analysis of variance) is a statistical procedure that allows you to determine if a set of categorical predictor variables can explain the variability in a set of continuous response variables. It is also possible to include continuous predictor variables either as covariates or as true independent variables in the design (so that you can test for the effect of interactions). MANOVA is related to within-subject ANOVA in that both of these analyses examine multiple measurements from each case (i.e., participant) in your data set. Whether you should perform a MANOVA or a within-subject ANOVA depends on the relationship between the measurements. If the different measurements reflect observations at different levels of a theoretical factor, then you should perform a within-subject ANOVA. For example, you might look at a person’s heart rate over successive days, such that the different measurements represent different levels of a "time" factor. If the me