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Statistical Programming in SAS

Statistical Programming in SAS Author A. John Bailer
ISBN-10 1607645041
Release 2010-06-01
Pages 460
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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.

Statistical Programming with SAS IML Software

Statistical Programming with SAS IML Software Author Rick Wicklin
ISBN-10 9781607647706
Release 2010-10-01
Pages 460
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Annotation SAS/IML software is a powerful tool for data analysts because it enables implementation of statistical algorithms that are not available in any SAS procedure. Rick Wicklin's Statistical Programming with SAS/IML Software is the first book to provide a comprehensive description of the software and how to use it. He presents tips and techniques that enable you to use the IML procedure and the SAS/IML Studio application efficiently. In addition to providing a comprehensive introduction to the software, the book also shows how to create and modify statistical graphs, call SAS procedures and R functions from a SAS/IML program, and implement such modern statistical techniques as simulations and bootstrap methods in the SAS/IML language. Written for data analysts working in all industries, graduate students, and consultants, Statistical Programming with SAS/IML Software includes numerous code snippets and more than 100 graphs.

SAS Statistics by Example

SAS Statistics by Example Author Ron Cody, EdD
ISBN-10 9781612900124
Release 2011-08-22
Pages 274
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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.

Simulating Data with SAS

Simulating Data with SAS Author Rick Wicklin
ISBN-10 9781629592534
Release 2013-04-22
Pages 362
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Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.

SAS for Data Analysis

SAS for Data Analysis Author Mervyn G. Marasinghe
ISBN-10 038777372X
Release 2008-12-10
Pages 558
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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.

SAS and R

SAS and R Author Ken Kleinman
ISBN-10 9781466584495
Release 2014-07-17
Pages 468
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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.

Elementary Statistics Using SAS

Elementary Statistics Using SAS Author Sandra D. Schlotzhauer
ISBN-10 1607644266
Release 2015-04-17
Pages 560
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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.

Handbook of SAS DATA Step Programming

Handbook of SAS   DATA Step Programming Author Arthur Li
ISBN-10 9781466552395
Release 2013-04-10
Pages 275
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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.

Learning SAS by Example

Learning SAS by Example Author Ron Cody
ISBN-10 9781635266566
Release 2018-07-03
Pages 536
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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.

SAS Applications Programming

SAS Applications Programming Author Frank C. DiIorio
ISBN-10 0534499708
Release 1997
Pages 684
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SAS Applications Programming has been writing in one form or another for most of life. You can find so many inspiration from SAS Applications Programming also informative, and entertaining. Click DOWNLOAD or Read Online button to get full SAS Applications Programming book for free.

Applied Statistics and the SAS Programming Language

Applied Statistics and the SAS Programming Language Author Ronald P. Cody
ISBN-10 0131465325
Release 2006
Pages 574
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As the SAS© programming language continues to evolve, this guide follows suit with timely coverage of the combination statistical package, database management system, and high-level programming language. Using current examples from business, medicine, education, and psychology, Applied Statistics and the SAS Programming Language is an invaluable resource for applied researchers, giving them the capacity to perform statistical analyses with SAS without wading through pages of technical documentation. Includes the necessary SAS statements to run programs for most of the commonly used statistics, explanations of the computer output, interpretations of results, and examples of how to construct tables and write up results for reports and journal articles. Illustrated with SAS Graph™ output. Provides readers with ample models for developing programming skills. For anyone interested in learning more about applied statistics and the SAS programming language.

Practical Statistical Methods

Practical Statistical Methods Author Lakshmi Padgett
ISBN-10 9781439812549
Release 2016-04-19
Pages 304
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Practical Statistical Methods: A SAS Programming Approach presents a broad spectrum of statistical methods useful for researchers without an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data. Omitting mathematical details and complicated formulae, the text provides SAS programs to carry out the necessary analyses and draw appropriate inferences for common statistical problems. After introducing fundamental statistical concepts, the author describes methods used for quantitative data and continuous data following normal and nonnormal distributions. She then focuses on regression methodology, highlighting simple linear regression, logistic regression, and the proportional hazards model. The final chapter briefly discusses such miscellaneous topics as propensity scores, misclassification errors, interim analysis, conditional power, bootstrap, and jackknife. With SAS code and output integrated throughout, this book shows how to interpret data using SAS and illustrates the many statistical methods available for tackling problems in a range of fields, including the pharmaceutical industry and the social sciences.

SAS Programming in the Pharmaceutical Industry

SAS Programming in the Pharmaceutical Industry Author Jack Shostak
ISBN-10 9781590478554
Release 2005-08-01
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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, Jack Shostak's SAS Programming in the Pharmaceutical Industry 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.

Data Analysis Using SAS

Data Analysis Using SAS Author C.Y. Joanne Peng
ISBN-10 9781483342795
Release 2008-08-28
Pages 640
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Data Analysis Using SAS offers a comprehensive core text focused on key concepts and techniques in quantitative data analysis using the most current SAS commands and programming language. The coverage of the text is more evenly balanced among statistical analysis, SAS programming, and data/file management than any available text on the market. It provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems. Designed to be used in order of teaching preference by instructor, the book is comprised of two primary sections: the first half of the text instructs students in techniques for data and file managements such as concatenating and merging files, conditional or repetitive processing of variables, and observations. The second half of the text goes into great depth on the most common statistical techniques and concepts - descriptive statistics, correlation, analysis of variance, and regression - used to analyze data in the social, behavioral, and health sciences using SAS commands. A student study at comes replete with a multitude of computer programs, their output, specific details on how to check assumptions, as well as all data sets used in the book. Data Analysis Using SAS is a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.

Basic Statistics Using SAS Enterprise Guide

Basic Statistics Using SAS Enterprise Guide Author Geoff Der
ISBN-10 9781599947150
Release 2007-11-01
Pages 240
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This example-rich guide shows you how to conduct a wide range of statistical analyses with no SAS programming required. For each analysis, one or more real data sets, a brief introduction of the technique, and a clear explanation of the SAS Enterprise Guide output are provided.

SAS Programming in the Pharmaceutical Industry Second Edition

SAS Programming in the Pharmaceutical Industry  Second Edition Author Jack Shostak
ISBN-10 9781629591490
Release 2014-03-01
Pages 308
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This comprehensive resource provides on-the-job training for statistical programmers who use SAS in the pharmaceutical industry This one-stop resource offers a complete review of what entry- to intermediate-level statistical programmers need to know in order to help with the analysis and reporting of clinical trial data in the pharmaceutical industry. SAS Programming in the Pharmaceutical Industry, Second Edition begins with an introduction to the pharmaceutical industry and the work environment of a statistical programmer. Then it gives a chronological explanation of what you need to know to do the job. It includes information on importing and massaging data into analysis data sets, producing clinical trial output, and exporting data. This edition has been updated for SAS 9.4, and it features new graphics as well as all new examples using CDISC SDTM or ADaM model data structures. Whether you're a novice seeking an introduction to SAS programming in the pharmaceutical industry or a junior-level programmer exploring new approaches to problem solving, this real-world reference guide offers a wealth of practical suggestions to help you sharpen your skills. This book is part of the SAS Press program.

Cody s Collection of Popular SAS Programming Tasks and How to Tackle Them

Cody s Collection of Popular SAS Programming Tasks and How to Tackle Them Author Ron Cody
ISBN-10 9781629597768
Release 2012-09-21
Pages 162
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Cody's Collection of Popular SAS Programming Tasks and How to Tackle Them presents often-used programming tasks that readers can either use as presented or modify to fit their own programs, all in one handy volume. Esteemed author and SAS expert Ron Cody covers such topics as character to numeric conversion, automatic detection of numeric errors, combining summary data with detail data, restructuring a data set, grouping values using several innovative methods, performing an operation on all character or all numeric variables in a SAS data set, and much more! SAS users of all levels interested in improving their programming skills will benefit from this easy-to-follow collection of tasks. This book is part of the SAS Press program.