 
  I am just joining this thread.  Regarding a tendency of journals to lock out the use of particular packages, there are rumours that SAS proc mixed has to be used for particular things.  I wonder if whether R might displace SAS or proc mixed in such a role could depend on wether there the QA provided by the R 
  contributed-packages system is felt to be as reliable as QA provided by something like SAS Institute. 
   
  Farrar
  
Jeffrey Robert Spies <jspies@nd.edu> wrote:
  As a student, I'll throw my two cents into this discussion. To 
preface my opinion, I am in a Joint Ph.D. program in Quantitative 
Psychology and Computer Science; I have a significant programming 
background and use R (or custom-built software that relies on R in 
some way) for the majority of my analyses.

In our psychology department, the stats courses are taught with a 
variety of statistical packages (SPSS, SAS, R, HLM, Mplus, Mx, etc.) 
with the hope of exposing students to a wide range of software. 
Professors in the department use an even wider range of packages for 
their own analyses. The truth of the matter is that you'll never be 
able to prepare students for every software package that they might 
have to use someday in the future. With that said, you can prepare 
your students to be able to learn these possible software packages in 
an efficient and timely manner by providing them with a firm 
background in statistics and giving them the basics of learning how 
to learn (not a typo) a new package, as not all social science 
students have a computer science background. In this way, I 
personally believe R is currently the best choice to start students 
with.

If students learn the basics of R, they're learning the basics of 
programming in a language similar to other non-statistical 
programming languages (for me, this alone is reason enough). 
Students will need to understand variables, functions, arguments, 
data types, data structures, loops, conditionals, etc. And if R is 
taught in a way that forces students to use the help function every 
once and a while and not have everything handed to them, they'll 
learn how to learn (again, not a typo) to use other packages (which 
may be another conversation entirely). Learning to use, read, and 
understand documentation is an under-taught and underestimated skill.

Also, if students really understand the statistics and can use R, 
they should be able to use the point and click packages with ease 
(that's why people use packages like SPSS). And if it is really such 
a concern that students have names like SPSS on their CVs, then why 
not spend one lab at the end of the semester running through a list 
of analyses previously done in R in SPSS. The reverse would be much 
more difficult if you plan to ensure comprehension.

I leave out all of the other reasons I'd choose R, because they've 
either been commented on or should be obvious (free, open-source, 
great community, grid-able, etc.) but one more thing Charilaos asked:

> I suppose one of the concerns in our case is whether people might be
> "locked out" so to speak in terms of being able to submit to certain
> journals or work with people who use one of these packages instead.
> Have any of you had any problems in that direction?

As an academic, statistician, and computer scientist, I will be 
horrified to find out that a journal would "lock out" a paper because 
of the software used to garner results (unless it was something like 
the Journal of Point and Click Statistics). In the majority of 
social science analyses, I would think it unnecessary for people to 
mention the software used in the first place--it's the analyses and 
their details that should matter. With that said, my lack of 
experience in a wide range of published journals may be showing through.

Regards,

Jeff.

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