I am not on the Statalist, but do take the Digest, so do not get the
listings until the following day. Most of the time I try to see what
has been discussed, sometimes i just don't have the time. Fortunately I
looked this morning.

Bob Muenchen of the Univ of Tennessee wrote a book a couple of years
ago titled "R for SAS and SPSS users" The folks at both SPSS and SAS
have seemed to love it, once they realized that the book was aimed to
help SAS/SPSS users who also wanted to learn R. It was not written to
convert anyone from SAS/SPSS to R. Bob is a SAS user and has no
intention of changing.

The statistics editor at Springer contacted me about working with Bob
for a book to be titled "R for Stata Users" He knew that I added R code
at the end of the chapters of my then recently published "Logistic
Regression Models" (May 2009, Chapman & Hall/CRC) which - insofar as it
was possible - was aimed to produce output corresponding to the Stata
examples I use throughout the text. I initially did this to assist
members of my classes with Statistics.com. I teach Logistic Regression
and Advanced Logistic Regression, as well as a couple of other courses
for them. Nearly all "students" are professors who teach statistics
courses in some discipline, or active researchers wanting to update
their knowledge of certain area of statistics. Many -- perhaps even
most -- of these students use R, with SAS as the next most common
sofware of preference. Very few come to class as Stata users. From the
feedback I get however, many of these students are so impressed with
what Stata can do that they end up as Stata users after the class is
over. They most definitely end up respecting Stata for its scope of
capabilities and ease of use. I have a 30 page tutorial on Stata as
Appendix A to help these students, and provide references to other
places where they can learn Stata, including the suite of Stata Press
books. Man times I have to tell them that there simply is no
corresponding SAS, SPSS, or R function available for some procedure we
are discussing.

It is clear in Logistic Regression Models that Stata has for more
modeling capabilities in this area than is available in R. I have a
couple of my later chapters which have no R examples at the end of
chapter, eg the chapter on exact logistic regression. But there are
areas in which someone has posted a library of functions to CRAN that
is not available in Stata; eg wavelets. I needed to write a NB2-NB1
hurdle model for a project a week ago. Stata does not have a command
for it, and I or anyone else I know has not written one, but it is
available using the flexmix function in R. This does not happen much,
but it can happen to any of us.

Now - to address the questions raised. I joined the project with Bob
because it is clear from email I get, from students and other profs I
relate with, and from what I see myself, that many - perhaps most -
textbooks now being published use R for examples. R is free and is not
a commercial package. Many university stat departments are now
requiring that their students learn R. And, from what I see being on
the editorial boards of 7 journals now, most examples used in Journals
employ R.

What does this mean? Well, as a long time committed Stata user (some 22
years now) it means that if I am going to get the most from textbooks
using R for examples, and if I am to better understand articles using R
for examples, then I want to understand the basics of R. If I am to
better help my R-using students to understand the Stata code and
examples I use in my books, I should know R so that i can use it to
teach them how to understand Stata and the examples. But there are some
models that are not yet available in Stata, but are available in R.

I didn't write the cover -- but the purpose of the book is to help
Stata users learn enough R to
1) better understand texts and journal articles employing R for
examples, and
2) to better be able to use R for the estimation of statistical
procedures that are currently unavailable in Stata. This includes how
to set up variables/observations, deal with missing values, and so
forth.

I can't imagine anyone actually switching from Stata to R, unless they
simply have no money to purchase the software and do not have access to
a university site license. there is nowhere in the book that advocates
such a change. In fact, for portions of the book that I wrote, I
compare Stata code with R code for doing some operation or functions.
Mostly Stata is easier - but sometimes not.

I myself find it much easier to use Stata than R for most commands and
operations. I too had trouble with the R "if"operator - because there
isn't any. this was difficult for me at first, but there are ways to
perform the operation that end up not so bad at all. However, Stata is
more direct.

The foremost area of instruction in "R for Stata Users" is perhaps data
management. This is the area that is most difficult for Stata users
trying to interpret R code that is presented in a text or article.
There are two chapters on graphics and one on basic statistical
commands, but nothing beyond linear regression and ANOVA.

The book is NOT for Stata users who have no reason to learn R. If it
were not for me having so many students who are R users and having to
present materials aimed to teach various statistical methods, and if I
did not want to better understand texts and journal articles that use
R, I would have no reason at all for learning it. Also, I referee more
articles than I have time for, in addition to my AE responsibilities,
and find that the majority of manuscripts I get use R for their
examples. In order to do a more responsible job as referee I felt that
I needed to learn R. But that has no bearing on what my preferred
statistical package is for my own work. It is clearly Stata - for a
host of reasons. But I still find it useful to know R as well. And that
is the point of the book. The book was written for those wanting to
augment Stata, or to better understand sources that use R for examples.