Learning to use SAS Enterprise Guide has never been easier! With The Little SAS Book for Enterprise Guide 4.1, Susan Slaughter and Lora Delwiche help you quickly become familiar with the SAS Enterprise Guide point-and-click environment. A series of carefully designed tutorials help you master the basics of the tasks you will want to do most frequently. The reference section of the book expands on the tutorial topics, focusing on specific features. If you are new to SAS or new to SAS Enterprise Guide, this book will be an invaluable tool on your way to becoming an expert.

Prepare for the SAS Base Programming for SAS®9 certification exam with the official guide by the SAS® Certified Professional Program. New and experienced SAS users who want to prepare for the SAS Base Programming for SAS®9 certification exam will find this guide an invaluable, convenient and comprehensive resource that covers all of the objectives tested on the exam. Major topics include importing and exporting raw data files, creating and modifying SAS data sets, and identifying and correcting data syntax and programming logic errors.You will also become familiar with the enhancements and new functionality that are available in SAS®9. Includes a free CD-ROM with tutorials, practice data, and sample programs to further reinforce and test your SAS skills.

At last! A real-world reference guide for clinical trial SAS programming, packed with solutions that programmers can apply to their day-to-day problems. Discover key techniques and tools available within Base SAS (including the macro language and PROC SQL), SAS/GRAPH, and SAS/STAT that can be used to resolve many common issues in working with clinical trial data. Organized to reflect the statistical programmer's work flow, this user-friendly text begins with an introduction to the working environment, then presents chapters on importing and massaging data into analysis data sets, producing clinical trial output, and exporting data. Valuable plug-and-play programming examples are provided throughout. Whether you're a novice seeking an introduction to SAS programming for the pharmaceutical industry or a junior-level programmer exploring new approaches to problem solving, you'll find a wealth of practical suggestions to help you sharpen your skills.

Jump-start your report-writing skills! Report writing has never been easier. Learn how you can easily avoid common report-writing pitfalls with SAS Guide to Report Writing: Examples, Second Edition. Updated for SAS®9, this task-oriented book guides you through the steps that you need to produce professional reports. Using a wealth of easy-to-follow examples, this time-saving book demonstrates the many different styles of reports that are available and the SAS tools used to generate them. The examples enable more experienced programmers to quickly grasp new techniques, while margin notes and additional discussions provide novice users with the details that they need for effective learning. You can save programming hours by using the SAS programs as they are or as models for developing your own reports. Whether you are a beginner or an expert, this must-have guide will strengthen your report-writing expertise and give you the tools that you need to enhance the power of your reports!

Updated for SA®9, this second edition is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics. Clear explanations and simple language guide you through the research terminology, data input, data manipulation, and types of statistical analysis that are most commonly used in the social and behavioral sciences. Providing practice data inspired by actual studies, this book teaches you how to choose the right statistic, understand the assumptions underlying the procedure, prepare the SAS program for the analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association. Step by step you will learn how to perform the following types of analysis: simple descriptive statistics, measures of bivariate association, t tests: independent samples and paired samples, NOVA and MANOVA, multiple regression, principal component analysis, and assessing scale reliability with coefficient alpha. This text is ideally suited to students who are beginning their study of data analysis, and to professors and researchers who want a handy reference on their bookshelf.

In Analysis of Clinical Trials Using SAS: A Practical Guide, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge the gap between modern statistical methodology and real-world clinical trial applications. Step-by-step instructions illustrated with examples from actual trials and case studies serve to define a statistical method and its relevance in a clinical trials setting and to illustrate how to implement the method rapidly and efficiently using the power of SAS software. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials, including analysis of stratified data, incomplete data, multiple inferences, issues arising in safety and efficacy monitoring, and reference intervals for extreme safety and diagnostic measurements. Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience compiled in this book. Numerous ready-to-use SAS macros and example code are included.

This book is part of the SAS Press program.

Master the language of PROC SQL! Get faster and better results when you use the SQL procedure with this step-by-step, example-driven guide in your hands. You will find information about implementing both American National Standards Institute (ANSI) guidelines and non-ANSI features. A broad range of SAS users, including applications programmers, database designers and administrators, statisticians, and systems analysts, will find techniques in Kirk Lafler's PROC SQL: Beyond the Basics Using SAS to enhance their data access, manipulation, and presentation prowess. Topics examined include database design; an introduction to SQL, dictionary tables, and tables; coding PROC SQL logic as well as complex queries; working with views; troubleshooting and debugging SQL code; and tuning for performance. With the growing popularity of databases, PROC SQL is becoming the language of choice for SAS users around the world. Intermediate and advanced users will appreciate the straightforward explanations and numerous examples.

Getting started with SAS is easy with The Little SAS Book. This friendly, easy-to-read guide gently introduces you to the most commonly used features of SAS software plus a whole lot more! The book has been revised to include concepts of the Output Delivery System; the STYLE= option in the PRINT, REPORT, and TABULATE procedures; ODS HTML, RTF, PRINTER, and OUTPUT destinations; PROC REPORT; more on PROC TABULATE; exporting data; and the colon modifier for informats. You'll find clear and concise explanations of basic SAS concepts (such as DATA and PROC steps), inputting data, modifying and combining data sets, summarizing and presenting data, basic statistical procedures, and debugging SAS programs. Each topic is presented in a self-contained, two-page layout complete with examples and graphics. This format enables new users to get up and running quickly, while the examples allow you to type in the program and see it work!

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.

Working with longitudinal data introduces a unique set of challenges. Once you've mastered the art of performing calculations within a single observation of a data set, you're faced with the task of performing calculations or making comparisons between observations. It's easy to look backward in data sets, but how do you look forward and across observations? Ron Cody provides straightforward answers to these and other questions. Longitudinal Data and SAS details useful techniques for conducting operations between observations in a SAS data set. For quick reference, the book is conveniently organized to cover tools, including an introduction to powerful SAS programming techniques for longitudinal data; case studies, including a variety of illuminating examples that use Ron's techniques; and macros, including detailed descriptions of helpful longitudinal data macros. Beginning to intermediate SAS users will appreciate this book's informative, easy-to-comprehend style. And users who frequently process longitudinal data will learn to make the most of their analyses by following Ron's methodologies.

This book is part of the SAS Press program.

The key to ensuring accurate data is having clean data. This book develops and describes data cleaning programs and macros. You can use many of the programs and macros that are provided, as is, or you can modify them for your own special data cleaning tasks. Ron has carefully explained and documented each of the programs and macros, thus providing you with SAS programming instruction on an intermediate-to-advanced level. Topics presented include validation checks on character data, numeric data, missing values, and date values; searching for duplicate records; working with multiple files; double entry and verification using the COMPARE procedure; and SQL solutions and using validation data sets. Written in Ron's signature informal, tutorial style, this book gives anyone who manages data thoroughly documented, step-by-step instructions for the development of data cleaning programs and macros. Supports releases 6.12 and higher of SAS software.

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, this book is for you! Informal and nontechnical, this book both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using the SAS System. Several social science real-world examples are included in full detail. This book also explains the differences and similarities among the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis with the PHREG procedure, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure to do loglinear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed. Supports releases 6.12 and higher of SAS software.

Real-world problems and data sets are the backbone of Ravindra Khattree and Dayanand Naik's Applied Multivariate Statistics with SAS Software, Second Edition, which provides a unique approach to the topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding IML procedure code, and covariance structures. The authors' approach to the information will aid professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding high-resolution output accompany sample problems, and clear explanations of SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples.

This book provides solutions to the problems in The SAS Workbook. Use it to compare your own programs to those created by the author of the problems workbook. Alternate solutions are offered for a number of the problems.

This book is part of the SAS Press program.

Learn by doing as you work through the programming problems offered in this unique book! Beginning with problems related to the DATA step, moving to elementary and then advanced exercises on frequently used SAS procedures, and also covering problems in statistical analysis, the book offers challenges for beginning, intermediate, and advanced programmers. Students, teachers, and trainers will be able to work with Base SAS procedures such as FORMAT, PRINT, TABULATE, and PLOT; solve simple descriptive statistics problems as well as those using the FREQ, TTEST, GLM, ANOVA, and NPAR1WAY procedures; and have fun with some SAS brainteasers in the book's last section. Each chapter gives readers a good start on solving the problem by providing directions and hints about useful programming tools. As a service to our educational market, look for The SAS Workbook Solutions sold separately. This book is part of the SAS Press program.

Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with this easy-to-read and comprehensive guide. Written for the reader with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical resource, ensuring that even the uninitiated becomes a sophisticated user of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered, such as time-dependent covariates, competing risks, and repeated events.