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SAS users in the Health and Life Sciences industry need to create complex graphs to analyze biostatistics data and clinical data, and they need to submit drugs for approval to the FDA. Graphs used in the HLS industry are complex in nature and require innovative usage of the graphics features. Clinical Graphs Using SAS® provides the knowledge, the code, and real-world examples that enable you to create common clinical graphs using SAS graphics tools, such as the Statistical Graphics procedures and the Graph Template Language. This book describes detailed processes to create many commonly used graphs in the Health and Life Sciences industry. For SAS® 9.3 and SAS® 9.4 it covers many improvements in the graphics features that are supported by the Statistical Graphics procedures and the Graph Template Language, many of which are a direct result of the needs of the Health and Life Sciences community. With the addition of new features in SAS® 9.4, these graphs become positively easy to create. Topics covered include the usage of SGPLOT procedure, the SGPANEL procedure and the Graph Template Language for the creation of graphs like forest plots, swimmer plots, and survival plots.
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.
Robert Allison's SAS/GRAPH: Beyond the Basics collects examples that demonstrate a variety of techniques you can use to create custom graphs using SAS/GRAPH software. SAS/GRAPH is known for its flexibility and power, but few people know how to use it to its full potential. Written for the SAS programmer with experience using Base SAS to work with data, the book includes examples that can be used in a variety of industry sectors. SAS/GRAPH: Beyond the Basics will help you create the exact graph you want.
The idea was to create a book useful for the day to day work as a consulting guide. To do so we created a book with a lot of code and explanations of the most common and not so common options that can help into the graphics production. All the figures presented in the book contain the code to be able to replicate, always using data available for everybody, such us using SASHELP library or generating our own data. At the same time, we tried that was accessible for all levels. It goes from a really basic level, explaining the SG procedures (SGPLOT, SGSCATTER and SGPANEL) and increasing in complexity little by little, showing how to extract the GTL code from the SG procedures, introducing PROC TEMPLATE and the different layouts, until we reach the final chapter where we create the shells for the most common figures, using all the learned to create common output requests.
Sanjay Matange and Dan Heath's Statistical Graphics Procedures by Example: Effective Graphs Using SAS shows the innumerable capabilities of SAS Statistical Graphics (SG) procedures. The authors begin with a general discussion of the principles of effective graphics, ODS Graphics, and the SG procedures. They then move on to show examples of the procedures' many features. The book is designed so that you can easily flip through it, find the graph you need, and view the code right next to the example. Among the topics included are how to combine plot statements to create custom graphs; customizing graph axes, legends, and insets; advanced features, such as annotation and attribute maps; tips and tricks for creating the optimal graph for the intended usage; real-world examples from the health and life sciences domain; and ODS styles. The procedures in Statistical Graphics Procedures by Example are specifically designed for the creation of analytical graphs. That makes this book a must-read for analysts and statisticians in the health care, clinical trials, financial, and insurance industries. However, you will find that the examples here apply to all fields. This book is part of the SAS Press program.
Provides usage information and examples for the Graph Template Language (GTL). The GTL is the underlying language for the default templates that are provided by SAS for procedures that use ODS Graphics. You can use the GTL either to modify these templates or to create your own highly customized charts and plots. Information covered includes how to combine language elements to build a custom graph, creating panels that contain multiple graphs, managing plot axes, using legends, modifying style elements to control appearance characteristics, and using functions, expressions, and conditional processing.
Create industry-compliant graphs with this practical guide for professionals Analysis of clinical trial results is easier when the data is presented in a visual form. However, clinical graphs must conform to specific guidelines in order to satisfy regulatory agency requirements. If you are a programmer working in the health care and life sciences industry and you want to create straightforward, visually appealing graphs using SAS, then this book is designed specifically for you. Written by two experienced practitioners, the book explains why certain graphs are requested, gives the necessary code to create the graphs, and shows you how to create graphs from ADaM data sets modeled on real-world CDISC pilot study data. SAS Graphics for Clinical Trials by Example demonstrates step-by-step how to create both simple and complex graphs using Graph Template Language (GTL) and statistical graphics procedures, including the SGPLOT and SGPANEL procedures. You will learn how to generate commonly used plots such as Kaplan-Meier plots and multi-cell survival plots as well as special purpose graphs such as Venn diagrams and interactive graphs. Because your graph is only as good as the aesthetic appearance of the output, you will learn how to create a custom style, change attributes, and set output options. Whether you are just learning how to produce graphs or have been working with graphs for a while, this book is a must-have resource to solve even the most challenging clinical graph problems.
Provides usage information and examples for the Graph Template Language (GTL). The GTL is the underlying language for the default templates that are provided by SAS for procedures that use ODS Graphics. You can use the GTL either to modify these templates or to create your own highly customized charts and plots. Information covered includes how to combine language elements to build a custom graph, creating panels that contain multiple graphs, managing plot axes, using legends, modifying style elements to control appearance characteristics, and using functions, expressions, and conditional processing.
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 that 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. Nearly every section has been revised to ensure that the sixth edition is fully up-to-date. This edition is also interface-independent, written for all SAS programmers whether they use SAS Studio, SAS Enterprise Guide, or the SAS windowing environment. New sections have been added covering PROC SQL, iterative DO loops, DO WHILE and DO UNTIL statements, %DO statements, using variable names with special characters, the ODS EXCEL destination, and the XLSX LIBNAME engine. This title belongs on every SAS programmer's bookshelf. It's a resource not just to get you started, but one you will return to as you continue to improve your programming skills. Learn more about the updates to The Little SAS Book, Sixth Edition here. Reviews for The Little SAS Book, Sixth Edition can be read here.
An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent Tasks The first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications. New to the Second Edition This edition now covers RStudio, a powerful and easy-to-use interface for R. It incorporates a number of additional topics, including using application program interfaces (APIs), accessing data through database management systems, using reproducible analysis tools, and statistical analysis with Markov chain Monte Carlo (MCMC) methods and finite mixture models. It also includes extended examples of simulations and many new examples. Enables Easy Mobility between the Two Systems Through the extensive indexing and cross-referencing, users can directly find and implement the material they need. SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Numerous example analyses demonstrate the code in action and facilitate further exploration. The datasets and code are available for download on the book’s website.