Features and capabilities of the REG, ANOVA, and GLM procedures are included in this introduction to analysing linear models with the SAS System. This guide shows how to apply the appropriate procedure to 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. This fourth edition includes updated examples, new software-related features, and new material, including a chapter on generalised linear models. Version 8 of the SAS System was used to run the SAS code examples in the book. * Provides clear explanations of how to use SAS to analyse linear models * Includes numerous SAS outputs * Includes new chapter on generalised linear models * Uses version 8 of the SAS system This book assists data analysts who use SAS/STAT software to analyse data using regression analysis and analysis of variance. It assumes familiarity with basic SAS concepts such as creating SAS data sets with the DATA step and manipulating SAS data sets with the procedures in base SAS software.

SAS for Linear Models

Science & Math

Stroup, Walter W.

Freund, Rudolf

Littell, Ramon

Mathematics

WA (Wiley-SAS)

Written in an informal and non-technical style, this book first explains the theory behind logistic regression and then shows how to implement it using the SAS System. Allison includes several detailed, real-world examples of the social sciences to provide readers with a better understanding of the material. He also explores the differences and similarities among the many generalizations of the logistic regression model.

Logistic Regression Using the SAS System: Theory and Application

Allison, Paul D.

Along with providing a useful discussion of categorical data analysis techniques, this book shows how to apply these methods with the SAS System. The authors include practical examples from a broad range of applications to illustrate the use of the FREQ, LOGISTIC, GENMOD, and CATMOD procedures in a variety of analyses. They also discuss other procedures such as PHREG and NPAR1WAY.

Categorical Data Analysis Using The SAS System

Davis, Charles S.

Stokes, Maura E.

Koch, Gary G.

Easy-to-read and comprehensive, this book shows how the SAS System performs multivariate time series analysis and features the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. The interrelationship of SAS/ETS procedures is demonstrated with an accompanying discussion of how the choice of a procedure depends on the data to be analysed and the reults desired. Other topics covered include detecting sinusoidal components in time series models and performing bivariate corr-spectral analysis and comparing the results with the standard transfer function methodology. The authors? unique approach to integrating students in a variety of disciplines and industries. Emphasis is on correct interpretation of output to draw meaningful conclusions. The volume, co-pubished by SAS and JWS, features both theory and practicality, and accompanies a soon-to-be extensive library of SAS hands-on manuals in a multitude of statistical areas. The book can be used with a number of hardware-specific computing machines including CMS, Mac, MVS, Opem VMS Alpha, Opmen VMS VAX, OS/390, OS/2, UNIX, and Windows.

SAS for Forecasting Time Series

Dickey, David A.

Brocklebank, John C.

This book describes how to use the SAS System to perform a wide variety of different regression analyses, such as using various models as well as diagnosing data problems. Topics include performing linear regression analyses using PROC REG; diagnosing and providing remedies for data problems including outliers and multicollinearity; using regression to fit a variety of different models, including nonlinear models; using SAS/INSIGHT software for performing regression analysis. Examples feature many SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others.

SAS(r) System for Regression, 3rd Edition

Computers & Technology

Software

One in a series of books co-published with SAS, this book provides a user-friendly introduction to both the SAS system and elementary statistical procedures for researchers and students in the Social Sciences. This Second Edition, updated to cover version 9 of the SAS software, guides readers step by step through the basic concepts of research and data analysis, to data input, and on to ANOVA (analysis of variance) and MANOVA (multivariate analysis of variance).

A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics

Norm O'Rourke

Larry Hatcher

Edward J. Stepanski

Filled with examples, Regression Using JMP?? introduces you to the basics of regression analysis using JMP?? software. You will learn how to perform regression analyses using a wide variety of models including linear and nonlinear models. Taking a tutorial approach, the author cover the customary Fit Y by X and Fit Model platforms, as well as the new features and capabilities of JMP?? Version 5, Output is covered in helpful detail. Thorough discussion of the following is also presented: * confidence limits * polynomial and smoothing models * examples using JMP?? scripting language * regression in the context of linear model methodology * diagnosis of and remedies for data problems including outliers and collinearity Statistical consultants familiar with regression analysis and with basic JMP concepts will appreciate the conversational, "what to look for" and "what if" scenarios presented. Non-Statisticians with a working knowledge of statistical concepts will learn to use JMP successfully for each analysis.

Regression Using JMP

Creighton, Lee

See the best price to sell, buy or rent books by the WA (Wiley-SAS) publisher. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by WA (Wiley-SAS)