handbook of sas r data step programming

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Handbook Of Sas Data Step Programming

Author : Arthur Li
ISBN : 9781466552395
Genre : Mathematics
File Size : 26. 88 MB
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To write an accomplished program in the DATA step of SAS®, programmers must understand programming logic and know how to implement and even create their own programming algorithm. Handbook of SAS® DATA Step Programming shows readers how best to manage and manipulate data by using the DATA step. The book helps novices avoid common mistakes resulting from a lack of understanding fundamental and unique SAS programming concepts. It explains that learning syntax does not solve all problems; rather, a thorough comprehension of SAS processing is needed for successful programming. The author also guides readers through a programming task. In most of the examples, the author first presents strategies and steps for solving the problem, then offers a solution, and finally gives a more detailed explanation of the solution. Understanding the DATA steps, particularly the program data vector (PDV), is critical to proper data manipulation and management in SAS. This book helps SAS programmers thoroughly grasp the concept of DATA step processing and write accurate programs in the DATA step. Numerous supporting materials, including data sets and programs used in the text, are available on the book’s CRC Press web page.

The Little Sas Book A Primer Fifth Edition

Author : Lora D. Delwiche
ISBN : 9781612904009
Genre : Mathematics
File Size : 35. 14 MB
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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.

Learning Sas By Example

Author : Ron Cody, EdD
ISBN : 9781599944265
Genre : Mathematics
File Size : 55. 24 MB
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Learn to program SAS by example! If you like learning by example, then Learning SAS by Example: A Programmer's Guide makes it easy to learn SAS programming. 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 Learning to use the SAS Output Delivery System Getting started with the SAS macro language Introducing PROC SQL You can test your knowledge and hone your skills by solving the problems at the end of each chapter. (Solutions to odd-numbered problems are located at the back of this book. Solutions to all problems are available to instructors by visiting Ron Cody's author page for details.) This book is intended for beginners and intermediate users. Readers should know how to enter and submit a SAS program from their operating system. This book is part of the SAS Press program.

Sas Hash Object Programming Made Easy

Author : Michele M. Burlew
ISBN : 9781612900988
Genre : Mathematics
File Size : 83. 94 MB
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Hash objects, an efficient look-up tool in the SAS DATA step, are object-oriented programming structures that function differently from traditional SAS language statements. Michele Burlew's SAS Hash Object Programming Made Easy shows readers how to use these powerful features, which they can program to quickly look up and manage data and to conserve computing resources. SAS provides various look-up techniques, and hash objects are among the newest, so therefore many users may not have yet used them. Because the examples presented vary in complexity, SAS Hash Object Programming Made Easy is useful to SAS users of all experience levels, from novice programmer to advanced programmer. Novice programmers can adapt some of the simpler hash programming techniques as they develop their SAS programming skills. This book helps more experienced programmers learn how to take advantage of hash object programming by comparing traditional processing techniques to those that use hash objects. Additionally, users from diverse fields with different requirements can adapt the examples in SAS Hash Object Programming Made Easy to fit their unique situations. This book is part of the SAS Press program.

The Sas Programmer S Proc Report Handbook Basic To Advanced Reporting Techniques

Author : Jane Eslinger
ISBN : 9781629602127
Genre : Computers
File Size : 31. 20 MB
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The SAS Programmer's PROC REPORT Handbook: Basic to Advanced Reporting Techniques is intended for programmers of all skill levels. Learn how to link multiple reports, add graphics and logos, and manipulate table of contents values to help refine your programs, macrotize where possible, troubleshoot easily, and get great-looking reports every time. From beginner to advanced, the examples in this book will help you harness all the power and capability of PROC REPORT. With dozens of useful examples, this book is completely unique in three ways. First, this book describes the default behavior of table of contents nodes and labels, and how to change the nodes inside of PROC REPORT. The chapter also explains how to use PROC DOCUMENT in conjunction with PROC REPORT. Secondly, an entire chapter is dedicated to the troubleshooting of errors, warnings, and notes that are produced by PROC REPORT, including explanations of what generated the log message and how to avoid it. Third, the book explains how to preprocess your data in order to get the best output from PROC REPORT, and it explores reports that require multiple steps to create. Whether you work in banking/finance, pharmaceuticals, the health and life sciences, or government, this handbook is sure to be your new favorite reporting reference.

Data Manipulation With R

Author : Phil Spector
ISBN : 9780387747309
Genre : Computers
File Size : 60. 12 MB
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This book presents a wide array of methods applicable for reading data into R, and efficiently manipulating that data. In addition to the built-in functions, a number of readily available packages from CRAN (the Comprehensive R Archive Network) are also covered. All of the methods presented take advantage of the core features of R: vectorization, efficient use of subscripting, and the proper use of the varied functions in R that are provided for common data management tasks. Most experienced R users discover that, especially when working with large data sets, it may be helpful to use other programs, notably databases, in conjunction with R. Accordingly, the use of databases in R is covered in detail, along with methods for extracting data from spreadsheets and datasets created by other programs. Character manipulation, while sometimes overlooked within R, is also covered in detail, allowing problems that are traditionally solved by scripting languages to be carried out entirely within R. For users with experience in other languages, guidelines for the effective use of programming constructs like loops are provided. Since many statistical modeling and graphics functions need their data presented in a data frame, techniques for converting the output of commonly used functions to data frames are provided throughout the book.

A Handbook Of Statistical Analyses Using R

Author : Torsten Hothorn
ISBN : 1420010654
Genre : Mathematics
File Size : 45. 45 MB
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R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Doing for R what Everitt's other Handbooks have done for S-PLUS, STATA, SPSS, and SAS, A Handbook of Statistical Analyses Using R presents straightforward, self-contained descriptions of how to perform a variety of statistical analyses in the R environment. From simple inference to recursive partitioning and cluster analysis, eminent experts Everitt and Hothorn lead you methodically through the steps, commands, and interpretation of the results, addressing theory and statistical background only when useful or necessary. They begin with an introduction to R, discussing the syntax, general operators, and basic data manipulation while summarizing the most important features. Numerous figures highlight R's strong graphical capabilities and exercises at the end of each chapter reinforce the techniques and concepts presented. All data sets and code used in the book are available as a downloadable package from CRAN, the R online archive. A Handbook of Statistical Analyses Using R is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

Longitudinal Data And Sas

Author : Ron Cody
ISBN : 1590474295
Genre : Computers
File Size : 85. 65 MB
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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-an introduction to powerful SAS programming techniques for longitudinal data; case studies-a variety of illuminating examples that use Ron's techniques; and macros-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.

Sas And R

Author : Ken Kleinman
ISBN : 9781466584495
Genre : Mathematics
File Size : 26. 90 MB
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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.

R For Dummies

Author : Andrie de Vries
ISBN : 9781119055839
Genre : Computers
File Size : 44. 99 MB
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Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more. R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide. Covers downloading, installing, and configuring R Includes tips for getting data in and out of R Offers advice on fitting regression models and ANOVA Provides helpful hints for working with graphics R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

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