ABSTRACT
This chapter presents the restricted multivariate general linear model that is really a mixture of the multivariate analysis of variance (MANOVA) and generalized MANOVA (GMANOVA) models. It describes how the seemingly unrelated regression (SUR) model may be used to estimate model parameters and to test hypotheses. The chapter also shows how the SUR model may be used to analyze the restricted GMANOVA model. The SUR model may also be used to estimate model parameters for multiple design multivariate regression models. The chapter illustrates how the SUR model may be used to estimate the parameters of the growth curve model and how to analyze data containing both cross-sectional and time series data. The SUR model may be used to represent numerous multivariate linear models as special cases. The SAS procedure provides numerous methods for estimating model parameters for a system of multiple regression equations.
