Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures in this invaluable edition of the comprehensive mixed models guide for data analysis, completely revised and updated for SAS®9. The theory underlying the models, the forms of the models for various applications and a wealth of examples from different fields of study are integrated in the discussions of theses models: - random effect only and random coefficients models, - split-plot, multilocation, and repeated measures models, - hierarchical models with nested random effects, - analysis of covariance models, - spatial correlation models, - generalized linear mixed models, - nonlinear mixed models. Professionals and students with a background in two-way ANOVA and regression and a basic knowledge of linear models and matrix algebra will benefit from the topics covered.
