SAS for Linear Models

This comprehensive introduction to analyzing linear models with the SAS System examines the features and capabilities of the REG, ANOVA and GLM procedures. Readers will learn how to apply the appropriate procedure to data analysis problems and understand PROC GLM output. In-depth discussions are also included on multivariate linear models, lack-of-fit analysis, covariance and heterogeneity of slopes, a classification with both crossed and nested effects, and analysis of variance for balanced data.

Ramon Littell and Walter W. Stroup are the authors of SAS for Linear Models, 4th Edition, published by Wiley.

Acknowledgments.

Chapter 1. Introduction.

Chapter 2. Regression.

Chapter 3. Analysis of Variance for Balanced Data.

Chapter 4. Analyzing Data with Random Effects.

Chapter 5. Unbalanced Data Analysis: Basic Methods.

Chapter 6. Understanding Linear Models Concepts.

Chapter 7. Analysis of Covariance.

Chapter 8. Repeated-Measures Analysis.

Chapter 9. Multivariate Linear Models.

Chapter 10. Generalized Linear Models.

Chapter 11. Examples of Special Applications.

References.

Index.

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SAS for Linear Models

Summary

Author Biography

Table of Contents

Supplemental Materials