Features and capabilities of the REG, ANOVA, and GLM procedures are included in this introduction to analyzing linear models with the SAS System. This clearly written guide will show you how to apply the appropriate procedure to your data analysis problems and understand PROC GLM output. Other helpful guidelines and discussions cover the following significant areas: 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. 
Supports releases 6.09 and higher of SAS software.

SAS System for Linear Models, Third Edition

Littell, Ramon C.

Computers & Technology

SAS Inst

At last! A comprehensive, applications-oriented mixed models guide for data analysis. Discover the latest capabilities available for a wide range of applications featuring the MIXED procedure in SAS/STAT software. This practical guide integrates the theory underlaying the models, the specific forms of the models for various applications, and examples from many different fields of study using appropriate SAS code with interpretation of results. 
Specific models discussed include: simple random-effect only, simple mixed with a single fixed and random effect, split-plot, multilocation, repeated measures, analysis of covariance, random coefficients, and spatial correlation. 
With a background in two-way ANOVA and regression and basic knowledge of linear models and matrix algebra, you will benefit from the discussion of basic to advanced topics in this book. A working knowledge of experimental design is also helpful. 
Supports releases 6.09 and higher of SAS software.

SAS System for Mixed Models

Stroup, Walter W.

Milliken, George A.

Wolfinger, Russell

Certification

Sandra Schlotzhauer and Ramon Littell's SAS System for Elementary Statistical Analysis, Second Edition, shows how to use SAS to perform basic statistical analysis. General topics include creating a data set with SAS; summarizing data with descriptive statistics, frequency tables, and bar charts; comparing groups (t-tests, one-way ANOVA, and nonparametric analogues); performing basic linear regression (lines, curves, and two-variable models); performing simple regression diagnostics (residuals plots, studentized residuals); and creating and analyzing tables of data. Using real-life examples, this beginner's guide bridges the gap between statistics texts and SAS documentation.

Sas System for Elementary Statistical Analysis

Schlotzhauer, Sandra D.

Operating Systems

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. This book is part of the SAS Press program.

SAS for Linear Models, Fourth Edition

Freund, Rudolf J.

Computer Science

SAS Institute

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