SAS for Linear Models / Edition 4

by Ramon C. Littell, Walter W. PH.D. Stroup, Rudolf Jakob Freund

Overview

This clear and comprehensive guide provides everything you need for powerful linear model analysis. Using a tutorial approach and plenty of examples, authors Ramon Littell, Walter Stroup, and Rudolf Freund lead you through methods related to analysis of variance with fixed and random effects. You will learn to use the appropriate SAS procedure for most experiment designs (including completely random, randomized blocks, and split plot) as well as factorial treatment designs and repeated measures. SAS for Linear Models, Fourth Edition, also includes analysis of covariance, multivariate linear models, and generalized linear models for non-normal data. Find inside: regression models; balanced ANOVA with both fixed- and random-effects models; unbalanced data with both fixed- and random-effects models; covariance models; generalized linear models; multivariate models; and repeated measures. New in this edition: MIXED and GENMOD procedures, updated examples, new software-related features, and other new material.

Product Details

ISBN-13:	9781590470237
Publisher:	SAS Institute Inc.
Publication date:	09/27/2010
Edition description:	4TH
Pages:	492
Product dimensions:	8.25(w) x 11.00(h) x 0.99(d)

Table of Contents

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

Editorial Reviews

A tutorial approach and many examples lead readers through methods related to analysis of variance with fixed and random effects and show how to choose the most appropriate SAS procedures for most experiment designs, such as completely random, randomized blocks, and split plot designs, as well as factorial treatment designs and repeated measures. Also covered are analysis of covariance, multivariate linear models, and generalized linear models for non-normal data. This fourth edition is updated to reflect the evolution of contemporary software and statistical analysis methods, covering MIXED and GENMOD procedures in detail. Littell teaches statistics at the University of Florida. Annotation c. Book News, Inc., Portland, OR (booknews.com)