This paper examines the multivariate multiple regression model and explores its applicability to communication research. The first section discusses partitioning of a data matrix, as a heuristic device for distinguishing among alternative regression models. Section two examines various aspects of univariate multiple regression, including the form of the model, the use of the model for descriptive purposes, the properties of estimators, the assumptions of the model, procedures for parameter estimation, procedures for hypothesis testing, interpretation of regression coefficients, and the need for reestimation. The third section offers a parallel presentation of aspects of multivariate multiple regression. A final section considers tests of assumptions, techniques for coping with failed assumptions, the relation of multivariate multiple regression to other multivariate procedures, and the advantages and disadvantages of multivariate multiple regression. (Author/AA)