Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory and Applications with SAS, Second Edition presents analyses of simple and complex models, both univariate and multivariate, that employ data sets from a variety of disciplines, such as the social and behavioral

Kevin Kim, Neil Timm

Preface. Overview of the General Linear Model. Unrestricted General Linear Models. Restricted General Linear Models. Weighted General Linear Models. Multivariate General Linear Models. Doubly Multivariate Linear Model. The Restricted MGLM and the Growth Curve Model. The SUR Model and the Restricted GMANOVA Model. Simultaneous Inference Using Finite Intersection Tests. Computing Power for Univariate and Multivariate GLM. Two-Level Hierarchical Linear Models. Incomplete Repeated Measurement Data. Structural Equation Modeling. References.