R for SAS and SPSS Users by Muenchen, Robert A.;

Series: Statistics and Computing;

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Product details:

Publisher Springer
Date of Publication 26 November 2008
Number of Volumes Book

ISBN 9780387094175
Binding Hardback
No. of pages470 pages
Size 235x155 mm
Weight 1900 g
Language English

Short description:

This book introduces R using SAS and SPSS terms. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R’s built-in functions. It compares and contrasts the differing approaches of all three packages.

Long description:

R is a powerful and free software system for data analysis and graphics, with over 1,200 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R’s built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages’ differing approaches. The programs and practice datasets are available for download.

The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. When finished, you will be able to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses.

"This is a really great book. It is easy to read, quite comprehensive, and would be extremely valuable to both regular R users and users of SAS and SPSS who wish to switch to or learn about R…An invaluable reference." - David Hitchcock, University of South Carolina

"Thanks for writing R for SAS and SPSS Users--it is a comprehensible and clever document. The graphics chapter is superb!" - Tony N. Brown, Vanderbilt University

"This is a Rosetta Stone for SPSS and SAS users to start learning R quickly and effectively." - Ralph O'Brien, ASA Fellow

"I am a professional SAS and SPSS programmer and found this book extremely useful." - Tony Chu, Public Policy Research Data Analyst

From the reviews
“This is a really great book. It is easy to read, quite comprehensive, and would be extremely valuable to both regular R users and users of SAS and SPSS who wish to switch to or learn about R…An invaluable reference.” - David Hitchcock, University of South Carolina
“Thanks for writing R for SAS and SPSS Users--it is a comprehensible and clever document. The graphics chapter is superb!” - Tony N. Brown, Vanderbilt University
"As his title suggests, Robert Muenchen crafted this to be a Rosetta Stone for SAS and SPSS users to start learning R quickly and effectively. Has he achieved this? Yes, and more." -Ralph O'Brien, Case Western Reserve University, ASA Fellow
“I am a professional SAS and SPSS programmer and found this book extremely useful.” - Tony Chu, Public Policy Research Data Analyst
"I found the book extremely helpful. Over the last few months I am regularly reaching for the book from my bookshelf to find sensible R code and to help with some data manipulation. The material is laid out in a way that makes it very accessible. Because of this I recommend this book to any R user regardless of his or her familiarity with SAS or SPSS. For those dedicated SAS and SPSS users I especially recommend the book. As discussed in the Introduction section, the basics of the R language are very different from SAS and SPSS but this book’s layout, style, and content help with these differences. The ordering of the material is very user-friendly and sensible...To new R users, and to R users of some years experience, I recommend this book. For new R users it will demystify many aspects, and for existing R users it will have many answers to those questions you have been too afraid to ask in public...." The American Statistician, February 2010, Vol. 64, No. 1
"The title of this book accurately describes its goal: to teach SAS and SPSS users how to use R...The book is laid out well, with sensible features such as a separate font for programs; tables listing complete programs in all three languages; an index with entries that include main SAS or SPSS commands and procedures, allowing users to locate R equivalents fairly quickly; and appendices comparing the three languages’ attributes and procedures/packages. It is much easier to read and likely comparably more helpful than a manual...There is no question in my mind that this can be a very useful book for its intended audience." Biometrics, 65, 1313, December 2009
"R for SAS and SPSS Users provides an excellent introduction to R. As Muenchen, Manager of the Statistical Computing Center at the University of Tennessee, notes in the Preface, the SPSS and SAS platforms, introduced over 30 years ago, have much in common – but are very different than 10 year old R. The book's first chapters focus on gentle GUI's for R before taking on the language starting in Chapter 8. At that point the book meticulously covers data management, data structures, programming, graphics and basic statistical analysis in R. The prose is clear, the examples tied to their SPSS and SAS analogs. The handling of both traditional and newer “ggplot2” graphics is comprehensive: SPSS and SAS users will undoubtedly find lots to like. The appendixes contrast R jargon with SPSS/SAS and compare SPSS/SAS products with the corresponding R packages." (Information Management, June 15, 2010)
“This book is designed for SAS/SPSS users interested in making a transition to R or wanting to add the additional capabilities of R to their repertoire. … book provides many simple how to s for new users of R and lots of comparative examples for users with knowledge of SAS and SPSS. … It is intended to help make the transition from SAS or SPSS to R as painless and smooth … .” (Roger M. Sauter, Technometrics, Vol. 53 (1), February, 2011)

Introduction. The five main parts of SAS and SPSS.- Programming conventions.- Typographic conventions.- Installing & updating R.- Running R.- Help and documentation.- Programming language basics.- Data Acquisition.- Selecting Variables - Var, Variables=.- Selecting observations - where, if select if, filter.- Selecting both variables and observations.- Converting data structures.- Data management.- Recoding variables. Value labels or formats (& measurement level).- Variable labels.- Generating data.- How R stores data.- Managing your files and workspace.- Graphics overview.- Traditional graphics.- The ggplot2 package.- Statistics.- Summary.- Conclusion.- Appendix A.- Appendix B.- Appendix C.- Bibliography.