Recommended Titles For Instructors»

Advanced Analytics/ Predictive Modeling

Below is a list of our recommended titles, organized by category. You can download the code and data for these books from the SAS Press Author Pages. Our online bookstore lists all available titles.

Advanced Analytics/Predictive Modeling

Involved in more advanced analytics and concepts? Consider these recommended titles for your classroom or personal reference library.

	Applied Multivariate Statistics with SAS Software, Second Edition By Ravindra Khattree, Ph.D., and Dayanand N. Naik, Ph.D. Includes information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding IML procedure code, and covariance structures. Together with Multivariate Data Reduction and Discrimination with SAS Software, provides comprehensive information about using SAS for multivariate statistics.		Categorical Data Analysis Using the SAS System, Third Edition By Maura Stokes, Charles Davis, and Gary Koch Provides a discussion of categorical data analysis techniques as well as an invaluable aid in applying these methods with SAS.
	Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition By Randall S. Collica In this instructive guide, Randy Collica employs SAS Enterprise Miner and the most commonly available techniques for customer relationship management (CRM).		Fixed Effects Regression Methods for Longitudinal Data Using SAS By Paul Allison, Ph.D. An invaluable resource for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques.
	Logistic Regression Using SAS: Theory and Application, Second Edition By Paul Allison This book both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using SAS; the second edition covers many new features of PROC LOGISTIC, as well as PROC SURVEYLOGISTIC, PROC GLIMMIX, PROC QLIM, and PROC MDC.		Multiple Comparisons and Multiple Tests Using SAS By Peter Westfall, Randall Tobias, and Russell Wolfinger Ideal for learning multiple comparisons procedures in standard linear models, multivariate analysis, categorical analysis, and regression and nonparametric statistics. Exercises available.
	Overdispersion Models in SAS By Jorge Morel and Nagaraj Neerchal This book provides a friendly methodology-based introduction to the ubiquitous phenomenon of overdispersion and features examples--many of which use the GLIMMIX, GENMOD, and NLMIXED procedures--covering a variety of fields of application.		Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications By Kattamuri Sarma This title addresses data collection and data cleaning, decision trees and regression trees, logistic regression models, neural networks, variable selection and variable transformation, and more.
	Regression and ANOVA: An Integrated Approach Using SAS Software By Keith E. Muller, Ph.D., and Bethel A. Fetterman, M.S. A graduate-level book that focuses on the general linear model (GLM) theory, stated in matrix terms, which provides a more compact, clear, and unified presentation of regression and ANOVA than do traditional sums of squares and scalar equations. Exercises included.		SAS for Forecasting Time Series, Second Edition By John C. Brocklebank, Ph.D., and David A. Dickey, Ph.D. A tutorial guide that demonstrates how SAS performs univariate and multivariate time series analysis.
	SAS System for Mixed Models, Second Edition By Ramon Littell, Ph.D., George Milliken, Ph.D., Walter Stroup,Ph.D., Russell Wolfinger, Ph.D., and Oliver Schabenberger, Ph.D. Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures. Completely revised and updated for SAS 9.		Simulating Data with SAS By Rick Wicklin A how-to book for statistical programmers who use SAS software and who want to simulate data efficiently.
	Statistical Programming with SAS/IML Software By Rick Wicklin Provides comprehensive description of the SAS/IML software and how to use it. Presents tips and techniques, with numerous code snippets and more than 100 graphs.		Survival Analysis Using SAS: A Practical Guide, Second Edition By Paul Allison, Ph.D. An easy-to-read and comprehensive guide for biomedical and social science researchers who want to analyze survival data with SAS.