ignoring the multiplex nature of social networks might result in sets of empirical findings that are misleading or contradictory. It would be helpful to adapt a variety of multivariate statistical techniques to handle network-oriented data. A canonical correlation analysis (CCA) makes a particularly interesting example since it is the most general form of the general linear model. In an example involving 317 banks, a CCA is applied to two multiplex networks: interdependence and cooperative alliances. Four significant patterns of association (orthogonal linear functions) are identified. (c) 2005 Elsevier B.V. All rights reserved.