An Introduction to SAS University Edition


Author: Ron Cody
Publisher: SAS Institute
ISBN: 1629600075
Category: Computers
Page: 366
View: 9692

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Get up and running with the SAS University Edition using Ron Cody’s easy-to-follow, step-by-step guide. Aimed at beginners who have downloaded the free SAS University Edition and want to either use the point-and-click interactive environment of SAS Studio, or who want to write their own SAS programs, or both, An Introduction to SAS University Edition, begins by showing you how to obtain the SAS University Edition, and how you can run SAS on a PC or Macintosh computer. The first part of the book shows you how to perform basic tasks, such as producing a report, summarizing data, producing charts and graphs, and using the SAS Studio built-in tasks. The first part also describes how you can perform basic statistical tests using the interactive point-and-click environment. The second part of the book shows you how to write your own SAS programs, and how to use SAS procedures to perform a variety of tasks. This part of the book also explains how to read data from a variety of sources: text files, Excel workbooks, and CSV files. In order to get familiar with the SAS Studio environment, this book also shows you how to access dozens of interesting data sets that are included with the product. Loading data files into SAS University Edition? Click here for more information.

An Introduction to SAS University Edition


Author: Ron Cody
Publisher: SAS Institute
ISBN: 1629600105
Category:
Page: 366
View: 7982

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Get up and running with the SAS University Edition using Ron Codya s easy-to-follow, step-by-step guide. Aimed at beginners who have downloaded the free SAS University Edition and want to either use the point-and-click interactive environment of SAS Studio, or who want to write their own SAS programs, or both, An Introduction to SAS University Edition, begins by showing you how to obtain the SAS University Edition, and how you can run SAS on a PC or Macintosh computer. The first part of the book shows you how to perform basic tasks, such as producing a report, summarizing data, producing charts and graphs, and using the SAS Studio built-in tasks. The first part also describes how you can perform basic statistical tests using the interactive point-and-click environment. The second part of the book shows you how to write your own SAS programs, and how to use SAS procedures to perform a variety of tasks. This part of the book also explains how to read data from a variety of sources: text files, Excel workbooks, and CSV files. In order to get familiar with the SAS Studio environment, this book also shows you how to access dozens of interesting data sets that are included with the product."

Essential Statistics Using SAS University Edition


Author: Geoff Der,Brian S. Everitt
Publisher: SAS Institute
ISBN: 1629600946
Category: Mathematics
Page: 246
View: 7627

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Students and instructors of statistics courses using SAS University Edition will welcome this book. Learning fundamental statistics is essential to solving problems with SAS. Essential Statistics Using SAS University Edition demonstrates how to use SAS University Edition to apply a variety of statistical methodologies, from the simple to the not-so-simple, to a range of data sets. Learn how to apply the appropriate statistical method to answer a particular question about a data set, and correctly interpret the numerical results that you obtain. SAS University Edition users who are new to SAS or who need a refresher course will benefit from the statistics overview and topics, such as multiple linear regression, logistic regression, and Poisson regression.

A Recipe for Success Using SAS University Edition

How to Plan Your First Analytics Project
Author: Sharon Jones
Publisher: SAS Institute
ISBN: 1629601942
Category: Computers
Page: 146
View: 8326

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Filled with helpful examples and real-life projects of SAS users, A Recipe for Success Using SAS University Edition is an easy guide on how to start applying the analytical power of SAS to real-world scenarios. This book shows you: how to start using analytics how to use SAS to accomplish a project goal how to effectively apply SAS to your community or school how users like you implemented SAS to solve their analytical problems A beginner’s guide on how to create and complete your first analytics project using SAS University Edition, this book is broken down into easy-to-read chapters that also include quick takeaway tips. It introduces you to the vocabulary and structure of the SAS language, shows you how to plan and execute a successful project, introduces you to basic statistics, and it walks you through case studies to inspire and motivate you to complete your own projects. Following a recipe for success using this book, harness the power of SAS to plan and complete your first analytics project!

Biostatistics by Example Using SAS Studio


Author: Ron Cody
Publisher: SAS Institute
ISBN: 1629604933
Category: Computers
Page: 262
View: 9583

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Learn how to solve basic statistical problems with Ron Cody's easy-to-follow style using the point-and-click SAS Studio tasks. Aimed specifically at the health sciences, Biostatistics by Example Using SAS Studio, provides an introduction to SAS Studio tasks. The book includes many biological and health-related problem sets and is fully compatible with SAS University Edition. After reading this book you will be able to understand temporary and permanent SAS data sets, and you will learn how to create them from various data sources. You will also be able to use SAS Studio statistics tasks to generate descriptive statistics for continuous and categorical data. The inferential statistics portion of the book covers the following topics: paired and unpaired t tests one-way analysis of variance N-way ANOVA correlation simple and multiple regression logistic regression categorical data analysis power and sample size calculations Besides describing each of these statistical tests, the book also discusses the assumptions that need to be met before running and interpreting these tests. For two-sample tests and N-way tests, nonparametric tests are also described. This book leads you step-by-step through each of the statistical tests with numerous screen shots, and you will see how to read and interpret all of the output generated by these tests. Experience with some basic statistical tests used to analyze medical data or classroom experience in biostatistics or statistics is required. Although the examples are related to the medical and biology fields, researchers in other fields such as psychology or education will find this book helpful. No programming experience is required. Loading data files into SAS University Edition? Click here for more information.

An Introduction to SAS Visual Analytics

How to Explore Numbers, Design Reports, and Gain Insight Into Your Data
Author: Tricia Aanderud,Rob Collum,Ryan Kumpfmiller
Publisher: SAS Institute
ISBN: 9781629602912
Category: Computers
Page: 294
View: 3633

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When it comes to business intelligence and analytical capabilities, SAS Visual Analytics is the premier solution for data discovery, visualization, and reporting. An Introduction to SAS Visual Analytics will show you how to make sense of your complex data with the goal of leading you to smarter, data-driven decisions without having to write a single line of code - unless you want to! You will be able to use SAS Visual Analytics to access, prepare, and present your data to anyone anywhere in the world. SAS Visual Analytics automatically highlights key relationships, outliers, clusters, trends and more. These abilities will guide you to critical insights that inspire action from your data. With this book, you will become proficient using SAS Visual Analytics to present data and results in customizable, robust visualizations, as well as guided analyses through auto-charting. With interactive dashboards, charts, and reports, you will create visualizations which convey clear and actionable insights for any size and type of data. This book largely focuses on the version of SAS Visual Analytics on SAS 9.4, although it is available on both 9.4 and SAS Viya platforms. Each version is considered the latest release, with subsequent releases planned to continue on each platform; hence, the Viya version works similarly to the 9.4 version and will look familiar. This book covers new features of each and important differences between the two. With this book, you will learn how to: Build your first report using the SAS Visual Analytics Designer Prepare a dashboard and determine the best layout Effectively use geo-spatial objects to add location analytics to reports Understand and use the elements of data visualizations Prepare and load your data with the SAS Visual Analytics Data Builder Analyze data with a variety of options, including forecasting, word clouds, heat maps, correlation matrix, and more Understand administration activities to keep SAS Visual Analytics humming along Optimize your environment for considerations such as scalability, availability, and efficiency between components of your SAS software deployment and data providers

SAS Essentials

Mastering SAS for Data Analytics
Author: Alan C. Elliott,Wayne A. Woodward
Publisher: John Wiley & Sons
ISBN: 1119042178
Category: Education
Page: 448
View: 8792

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A step-by-step introduction to using SAS® statistical software as a foundational approach to data analysis and interpretation Presenting a straightforward introduction from the ground up, SAS® Essentials: Mastering SAS for Data Analytics, Second Edition illustrates SAS using hands-on learning techniques and numerous real-world examples. Keeping different experience levels in mind, the highly-qualified author team has developed the book over 20 years of teaching introductory SAS courses. Divided into two sections, the first part of the book provides an introduction to data manipulation, statistical techniques, and the SAS programming language. The second section is designed to introduce users to statistical analysis using SAS Procedures. Featuring self-contained chapters to enhance the learning process, the Second Edition also includes: Programming approaches for the most up-to-date version of the SAS platform including information on how to use the SAS University Edition Discussions to illustrate the concepts and highlight key fundamental computational skills that are utilized by business, government, and organizations alike New chapters on reporting results in tables and factor analysis Additional information on the DATA step for data management with an emphasis on importing data from other sources, combining data sets, and data cleaning Updated ANOVA and regression examples as well as other data analysis techniques A companion website with the discussed data sets, additional code, and related PowerPoint® slides SAS Essentials: Mastering SAS for Data Analytics, Second Edition is an ideal textbook for upper-undergraduate and graduate-level courses in statistics, data analytics, applied SAS programming, and statistical computer applications as well as an excellent supplement for statistical methodology courses. The book is an appropriate reference for researchers and academicians who require a basic introduction to SAS for statistical analysis and for preparation for the Basic SAS Certification Exam.

Statistical Programming in SAS


Author: A. John Bailer
Publisher: SAS Institute
ISBN: 9781607645047
Category: Computers
Page: 460
View: 4452

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In this guide, the author integrates SAS tools with interesting statistical applications and uses SAS 9.2 as a platform to introduce programming ideas for statistical analysis, data management, and data display and simulation.

The Little SAS Book

A Primer, Fifth Edition
Author: Lora D. Delwiche,Susan J. Slaughter
Publisher: SAS Institute
ISBN: 1612904009
Category: Computers
Page: 376
View: 6292

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A classic that just keeps getting better, The Little SAS Book is essential for anyone learning SAS programming. Lora Delwiche and Susan Slaughter offer a user-friendly approach so readers can quickly and easily learn the most commonly used features of the SAS language. Each topic is presented in a self-contained two-page layout complete with examples and graphics. The fifth edition has been completely updated to reflect the new default output introduced with SAS 9.3. In addition, there is a now a full chapter devoted to ODS Graphics including the SGPLOT and SGPANEL procedures. Other changes include expanded coverage of linguistic sorting and a new section on concatenating macro variables with other text. This book is a great tool for users of SAS 9.4 as well. This title belongs on every SAS programmer's bookshelf. It's a resource not just to get you started, but one you'll return to as you continue to improve your programming skills. This book is part of the SAS Press program.

Elementary Statistics Using SAS


Author: Sandra D. Schlotzhauer
Publisher: SAS Institute
ISBN: 1629597937
Category: Mathematics
Page: 560
View: 9063

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Bridging the gap between statistics texts and SAS documentation, Elementary Statistics Using SAS is written for those who want to perform analyses to solve problems. The first section of the book explains the basics of SAS data sets and shows how to use SAS for descriptive statistics and graphs. The second section discusses fundamental statistical concepts, including normality and hypothesis testing. The remaining sections of the book show analyses for comparing two groups, comparing multiple groups, fitting regression equations, and exploring contingency tables. For each analysis, author Sandra Schlotzhauer explains assumptions, statistical approach, and SAS methods and syntax, and makes conclusions from the results. Statistical methods covered include two-sample t-tests, paired-difference t-tests, analysis of variance, multiple comparison techniques, regression, regression diagnostics, and chi-square tests. Elementary Statistics Using SAS is a thoroughly revised and updated edition of Ramon Littell and Sandra Schlotzhauer's SAS System for Elementary Statistical Analysis.

SAS Statistics by Example


Author: Ron Cody, EdD
Publisher: SAS Institute
ISBN: 1612900127
Category: Computers
Page: 274
View: 8500

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In SAS Statistics by Example, Ron Cody offers up a cookbook approach for doing statistics with SAS. Structured specifically around the most commonly used statistical tasks or techniques--for example, comparing two means, ANOVA, and regression--this book provides an easy-to-follow, how-to approach to statistical analysis not found in other books. For each statistical task, Cody includes heavily annotated examples using ODS Statistical Graphics procedures such as SGPLOT, SGSCATTER, and SGPANEL that show how SAS can produce the required statistics. Also, you will learn how to test the assumptions for all relevant statistical tests. Major topics featured include descriptive statistics, one- and two-sample tests, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and sample size. This is not a book that teaches statistics. Rather, SAS Statistics by Example is perfect for intermediate to advanced statistical programmers who know their statistics and want to use SAS to do their analyses. This book is part of the SAS Press program.

Cody's Data Cleaning Techniques Using SAS, Second Edition


Author: Ron Cody
Publisher: SAS Institute
ISBN: 1629597732
Category: Mathematics
Page: 268
View: 640

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Thoroughly updated for SAS 9, Cody's Data Cleaning Techniques Using SAS, Second Edition, addresses tasks that nearly every SAS programmer needs to do - that is, make sure that data errors are located and corrected. Written in Ron Cody's signature informal, tutorial style, this book develops and demonstrates data cleaning programs and macros that you can use as written or modify for your own special data cleaning needs. Each topic is developed through specific examples, and every program and macro is explained in detail.

Statistical Graphics in SAS

An Introduction to the Graph Template Language and the Statistical Graphics Procedures
Author: Warren F. Kuhfeld
Publisher: Sas Inst
ISBN: 9781607644859
Category: Computers
Page: 211
View: 1047

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The Graph Template Language (GTL) and the Statistical Graphics (SG) procedures are powerful new additions to SAS for creating high-quality statistical graphics. Warren F. Kuhfeld's "Statistical Graphics in SAS: An Introduction to the Graph Template Language and the Statistical Graphics Procedures" provides a parallel and example-driven introduction to the SG procedures and the GTL. Most graphs in the book are produced in at least two ways. Each example provides prototype code for getting started with the GTL and with the SG procedures. While you do not need to write a template to make many useful graphs, understanding the GTL enables you to create custom graphs that cannot be produced by the SG procedures. Knowing the GTL also helps you modify the sometimes complex templates that SAS provides. Written for anyone interested in statistical graphics, Statistical Graphics in SAS is a comprehensive introduction to these two aspects of ODS Graphics. It helps you understand the basics of what you can do with the SG procedures as well as how you can go beyond that by using the full power of the GTL.

Learning SAS by Example

A Programmer's Guide, Second Edition
Author: Ron Cody
Publisher: SAS Institute
ISBN: 1635266564
Category: Computers
Page: 536
View: 7406

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Learn to program SAS by example! Learning SAS by Example, A Programmer’s Guide, Second Edition, teaches SAS programming from very basic concepts to more advanced topics. Because most programmers prefer examples rather than reference-type syntax, this book uses short examples to explain each topic. The second edition has brought this classic book on SAS programming up to the latest SAS version, with new chapters that cover topics such as PROC SGPLOT and Perl regular expressions. This book belongs on the shelf (or e-book reader) of anyone who programs in SAS, from those with little programming experience who want to learn SAS to intermediate and even advanced SAS programmers who want to learn new techniques or identify new ways to accomplish existing tasks. In an instructive and conversational tone, author Ron Cody clearly explains each programming technique and then illustrates it with one or more real-life examples, followed by a detailed description of how the program works. The text is divided into four major sections: Getting Started, DATA Step Processing, Presenting and Summarizing Your Data, and Advanced Topics. Subjects addressed include Reading data from external sources Learning details of DATA step programming Subsetting and combining SAS data sets Understanding SAS functions and working with arrays Creating reports with PROC REPORT and PROC TABULATE Getting started with the SAS macro language Leveraging PROC SQL Generating high-quality graphics Using advanced features of user-defined formats and informats Restructuring SAS data sets Working with multiple observations per subject Getting started with Perl regular expressions You can test your knowledge and hone your skills by solving the problems at the end of each chapter.

Intensive Longitudinal Methods

An Introduction to Diary and Experience Sampling Research
Author: Niall Bolger,Jean-Philippe Laurenceau
Publisher: Guilford Press
ISBN: 1462506925
Category: Psychology
Page: 256
View: 2135

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This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website (www.intensivelongitudinal.com).

SAS for Data Analysis

Intermediate Statistical Methods
Author: Mervyn G. Marasinghe,William J. Kennedy
Publisher: Springer Science & Business Media
ISBN: 9780387773728
Category: Mathematics
Page: 558
View: 1604

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This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Business Survival Analysis Using SAS

An Introduction to Lifetime Probabilities
Author: Jorge Ribeiro
Publisher: SAS Institute
ISBN: 1629605190
Category: Computers
Page: 236
View: 6418

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Solve business problems involving time-to-event and resulting probabilities by following the modeling tutorials in Business Survival Analysis Using SAS®: An Introduction to Lifetime Probabilities, the first book to be published in the field of business survival analysis! Survival analysis is a challenge. Books applying to health sciences exist, but nothing about survival applications for business has been available until now. Written for analysts, forecasters, econometricians, and modelers who work in marketing or credit risk and have little SAS modeling experience, Business Survival Analysis Using SAS® builds on a foundation of SAS code that works in any survival model and features numerous annotated graphs, coefficients, and statistics linked to real business situations and data sets. This guide also helps recent graduates who know the statistics but do not necessarily know how to apply them get up and running in their jobs. By example, it teaches the techniques while avoiding advanced theoretical underpinnings so that busy professionals can rapidly deliver a survival model to meet common business needs. From first principles, this book teaches survival analysis by highlighting its relevance to business cases. A pragmatic introduction to survival analysis models, it leads you through business examples that contextualize and motivate the statistical methods and SAS coding. Specifically, it illustrates how to build a time-to-next-purchase survival model in SAS® Enterprise Miner, and it relates each step to the underlying statistics and to Base SAS® and SAS/STAT® software. Following the many examples—from data preparation to validation to scoring new customers—you will learn to develop and apply survival analysis techniques to scenarios faced by companies in the financial services, insurance, telecommunication, and marketing industries, including the following scenarios: Time-to-next-purchase for marketing Employer turnover for human resources Small business portfolio macroeconometric stress tests for banks International Financial Reporting Standard (IFRS 9) lifetime probability of default for banks and building societies "Churn," or attrition, models for the telecommunications and insurance industries

Beginning R

An Introduction to Statistical Programming
Author: Larry Pace,Joshua Wiley
Publisher: Apress
ISBN: 1484203739
Category: Computers
Page: 327
View: 4770

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Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3. R is a powerful open-source language and programming environment for statistics and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for data analysis and research. What You Will Learn: How to acquire and install R Hot to import and export data and scripts How to analyze data and generate graphics How to program in R to write custom functions Hot to use R for interactive statistical explorations How to conduct bootstrapping and other advanced techniques

An Introduction to Statistical Learning

with Applications in R
Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
Publisher: Springer Science & Business Media
ISBN: 1461471389
Category: Mathematics
Page: 426
View: 9393

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Multilevel Analysis

An Introduction to Basic and Advanced Multilevel Modeling
Author: Tom A B Snijders,Roel J Bosker
Publisher: SAGE
ISBN: 144625433X
Category: Reference
Page: 368
View: 505

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The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker's book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.