[R] things that are difficult/impossible to do in SAS or SPSS butsimple in R
Greg Snow
Greg.Snow at imail.org
Tue Jan 15 21:58:13 CET 2008
My SAS and SPSS are rusty as well, so things may have changed, but I
think it is still difficult to do simulations and general bootstrap type
analyses (simulate or resample a dataset, analyze it and capture a piece
(or pieces) of the output, repeate many times and end up with a
vector/matrix of interest).
Some aspects of graphics, adding to graphs I believe is still quite a
bit easier in R/S-PLUS.
Show some interactive graphics, start with simple things like the
identify function, up to more complex examples (some in the
TeachingDemos package as well as other places), also look at the iplots
and rgl packages.
I (and I expect others here) am interested in what you find, maybe you
could post a link to your finished presentation after you give it.
Those are the things that come to my mind first, hope it helps,
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
(801) 408-8111
> -----Original Message-----
> From: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] On Behalf Of Matthew Keller
> Sent: Tuesday, January 15, 2008 12:45 PM
> To: R Help
> Subject: [R] things that are difficult/impossible to do in
> SAS or SPSS butsimple in R
>
> Hi all,
>
> I'm giving a talk in a few days to a group of psychology
> faculty and grad students re the R statistical language. Most
> people in my dept.
> use SAS or SPSS. It occurred to me that it would be nice to
> have a few concrete examples of things that are fairly
> straightforward to do in R but that are difficult or
> impossible to do in SAS or SPSS. However, it has been so long
> since I have used either of those commercial products that I
> am drawing a blank. I've searched the forums and web for a
> list and came up with just Bob Muenchen's comparison of
> general procedures and Patrick Burns' overview of the three.
> Neither of these give concrete examples of statistical
> problems that are easily solved in R but not the commercial packages.
>
> Can anyone more familiar with SAS or SPSS think of some
> examples of problems that they couldn't do in one of those
> packages but that could be done easily in R? Similarly, if
> there are any examples of the converse I would also be
> interested to know.
>
> Best,
>
> Matt
>
> --
> Matthew C Keller
> Asst. Professor of Psychology
> University of Colorado at Boulder
> www.matthewckeller.com
>
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