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).
|Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications|
By Iain Brown
Combine complex concepts facing the financial sector with the software toolsets available to analysts.
|Decision Trees for Analytics Using SAS Enterprise Miner
By Barry de Ville and Padraic Neville
An expanded and enhanced resource which provides the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. Users will be able to make recommendations from decision trees and search algorithms in order to improve and customize their segmentation of the market.
|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.
|Fundamentals of Predictive Analytics with JMP
By Ron Klimberg and B. D. McCullough
With the new emphasis on business intelligence, business analytics and predictive analytics, Fundamentals of Predictive Analytics with JMP is invaluable to everyone who needs to expand their knowledge of statistics and apply real problem-solving analysis.
|Logistic Regression Using SAS: Theory and Application, Second Edition|
By Paul Allison, Ph.D.
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
|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.
|Practical Time Series Analysis Using SAS
By Anders Milhøj
Explains and demonstrates through examples how you can use SAS for time series analysis. It offers modern procedures for forecasting, seasonal adjustments, and decomposition of time series that can be used without involved statistical reasoning.
|Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second Edition
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.
|PROC SQL: Beyond the Basics Using SAS, Second Edition
By Kirk Paul Lafler
From designing database tables to tuning for performance and efficiency, this second edition delves into the workings of PROC SQL with greater analysis and discussion. Includes unique application-oriented code along with real-world examples of a powerful relational database interface language.
|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.
|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.
|Segmentation and Lifetime Value Models Using SAS
By Edward Malthouse
Learn how to perform analyses to identify customers and make informed marketing investments. This book answers core questions on customer relationship management (CRM), provides an overall framework for thinking about CRM, and offers real-world examples across a variety of industries.
|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.