Canonical correlation analysis is a useful and powerful technique for exploring the relationships among multiple dependent and independent variables. The technique is primarily descriptive, although it may be used for predictive purposes.  It is useful for identifying overall relationships between multiple independent and dependent variables, particularly when the data researcher has little a priori knowledge about relationships among the sets of variables.

     SEM is a statistical technique that combines elements of traditional multivariate models, such as
regression analysis, factor analysis, and simultaneous equation modeling. SEM is a largely confirmatory, rather than exploratory, technique. That is, a researcher are more likely to use SEM to determine whether a certain model is valid., rather than using SEM to "find" a suitable model--although SEM analyses often involve a certain exploratory element.