R for SAS and SPSS Users (Statistics and Computing) (Hardcover)

~ Robert A. Muenchen (Author)
Key Phrases: workshop attendance, statistics package, filter table, Data Management, Springer Science, Business Media (more...)

Editorial Reviews

Review

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

"Readership: Users of SAS or SPSS who want to learn the basics of R. The author is the manager of the Statistical Consulting Center at the University of Tennessee and has been consulting in statistics for over 25 years. … The author introduces a number of useful packages in his text … ." (Joseph G. Voelkel, International Statistical Review, Vol. 77 (3), 2009)

"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

Product 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

Product Details

• Hardcover: 470 pages
• Publisher: Springer; 1 edition (October 24, 2008)
• Language: English
• ISBN-10: 0387094172
• ISBN-13: 978-0387094175
• Product Dimensions: 9.3 x 6.1 x 1 inches
• Shipping Weight: 1.8 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (6 customer reviews)
• Amazon.com Sales Rank: #222,669 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

7 of 7 people found the following review helpful:

5.0 out of 5 stars Reviews from Journals, November 3, 2008

By	Robert A. Muenchen "Bob Muenchen" (Knoxville, TN USA) - See all my reviews (REAL NAME)

I'm the author posting summaries of some journal reviews. You can read many other reviews and download the example programs at the book's web site, r4stats.com. Cheers, Bob Muenchen

"...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

5 of 5 people found the following review helpful:

5.0 out of 5 stars From SAS to R made easy, January 15, 2009

By	I Teach Typing (Stanford, CA USA) - See all my reviews

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This book is absolutely excellent. The focus is on the data manipulation and processing that goes on before analysis. As a longtime SAS user, this is the major stumbling block for me using R. The parallels and discrepancies across the languages are clearly pointed out with solid code examples. The book covers basic syntax but more importantly it goes way beyond saying this is the syntax for an "if" statement in SAS and this is an "if" statement in R. The author goes into the important fundamental differences in how the two languages think about and process data.[...]

There is also very good coverage of R graphics (especially the set of functions in ggplot2 that are wildly useful and rarely mentioned in other books). The coverage of statistics is limited to only one chapter. So, do not get the book if you only want to learn the ins-and-outs of R stats. Happily that chapter covers the most commonly done statistics. So even in its short presentation it should help everyone.

While the book is geared toward someone with experience in SAS or SPSS, I think it would be excellent for anyone learning R. The links to the point and click versions of R (R commander, Rattle or JGR) are invaluable for anyone starting out.

The author is actively maintaining the book's website. So be sure to grab the errata and his notes.

5 of 5 people found the following review helpful:

5.0 out of 5 stars Great read for SPSS or SAS users learning R, January 6, 2009

By	E. Warren Lambert "E. Warren Lambert" (Nashville, Tennessee) - See all my reviews (REAL NAME)

Amazon Verified Purchase

I've used and taught SAS and SPSS since about 1982. It seems to me that much of the new statistical developments are coming out in the open-source R language, rather than business-prediction software like SAS or SPSS. The number of new statistical packages in R is rapidly increasing, including packages supported by high quality textbooks. SAS and SPSS offer "business intelligence" -- software to help businessmen predict the future -- rather than cutting-edge tools for serious research.

There are many good books for R experts, and good beginners books are starting to come out. Before Muenchen's book, there was nothing to help the experienced SAS/SPSS programmer learn R. Since R is object-oriented, it "thinks" quite differently from SAS and SPSS, and you spend as much time unlearning old ways of thinking as learning new ones.

The author of R FOR SAS AND SPSS USERS knows how SAS/SPSS programmers think, since he is one of us and has spent decades at UT teaching people to manage and analyze data in SAS, SPSS, and other software. This makes his explanations seem intuitive and natural without the "one hand clapping" feeling you get from R "help" messages. The book is not only a good introduction but it goes into considerable detail to cover basic and intermediate R programming. The style is simple and lucid. Unlike some R material, the book is rich in concrete examples. Each chapter has 3 tables of similar code in SAS, SPSS, and R. These tables may help it serve as a "lookup book" during programming.

I keep a text file of the book's examples open in my editor when I write R code so that I can cut and paste working code from the book rather than doing trial and error on minor details. This same cut-and-paste approach works with SAS, SPSS, and other software.

If you have some years with SAS or SPSS and you want to learn R, this will be your #1 book.