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re: st: R for Stata Users


From   "Airey, David C" <david.airey@Vanderbilt.Edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   re: st: R for Stata Users
Date   Fri, 26 Feb 2010 08:42:48 -0600

.

Scott Merryman posted 1/14/10 with no replies:

> R for Stata Users
> Series: Statistics and Computing
> Muenchen, Robert A., Hilbe, Joseph M.
> 
> 2010, Approx. 565 p., Hardcover
> 
> ISBN: 978-1-4419-1317-3
> 
> Not yet published. Available: March 21, 2010
> 
> 
> http://www.springer.com/statistics/computational/book/978-1-4419-1317-3

Apparently Stata has "jargon", and R has "formal" terminology. R also has "publication quality graphs". Why does everyone keep saying this as if these are somehow unavailable in other packages? It is easier to make a crappy graph in R than Stata in my hands at least. Also, if I were a professional Stata user, why the hell would I want to know how to do basic statistics and basic graphs in R? There are now 900 books describing such. Rather I might want to know how to use R to extend Stata with packages unavailable in Stata and outside my expertise to do so, period.

Maybe one of the authors can comment on the title.

--snip--
	• Read data from various types of text files and Stata data sets
	• Manage your data through transformations, recodes, and combining data sets from both the add-cases and add-variables approaches and restructuring data from wide to long formats and vice versa
	• Create publication quality graphs including bar, histogram, pie, line, scatter, regression, box, error bar, and interaction plots
	• Perform the basic types of analyses to measure strength of association and group differences and be able to know where to turn to cover much more complex methods

Stata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to extend the power of Stata through the use of R. It introduces R using Stata terminology with which you are already familiar. It steps through more than 30 programs written in both languages, comparing and contrasting the two packages' different approaches. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses.

A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.

Robert A. Muenchen is the author of the book, R for SAS and SPSS Users, and is a consulting statistician with 29 years of experience. He has served on the advisory boards of SAS Institute, SPSS Inc., and the Statistical Graphics Corporation. He currently manages Research Computing Support at The University of Tennessee.

Joseph M. Hilbe is Solar System Ambassador with NASA/Jet Propulsion Laboratory, California Institute of Technology, an adjunct professor of statistics at Arizona State, and emeritus professor at the University of Hawaii. He is a Fellow of the American Statistical Association and elected member of the International Statistical Institute. Hilbe was the first editor of the Stata Technical Bulletin, (later named the Stata Journal) and is author of a number of textbooks, including Logistic Regression Models and Negative Binomial Regression.

Written for » Professional/practitioner
--snip--



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