The indispensable, up-to-date guide to mixed models using SASŪ. Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures in this valuable edition of the comprehensive mixed models guide for data analysis, completely revised and updated for SASŪ9. 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 these 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
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