[R] I need arguments pro-S-PLUS and against SAS...

Tue Jan 8 17:09:28 CET 2008

A good summary of the differences between S-PLUS and SAS, along with
their respective advantages and disadvantages, is given in Section 1.6
of http://lib.stat.cmu.edu/S/Harrell/doc/splusp.pdf.

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of bogdan romocea
Sent: Tuesday, January 08, 2008 9:08 AM
To: jsorkin at grecc.umaryland.edu
Cc: r-help
Subject: Re: [R] I need arguments pro-S-PLUS and against SAS...

> John Sorkin wrote:
> The difference is not so much the language as the end users.
> S-Plus, R, SAS, etc. are all similar in that they are all tools to an 
> end and not an end in themselves.

Try to find one user who:
  1. is familiar with both SAS and R/S-Plus;
  2. has to do real data analysis work (i.e., other than following
pre-canned procedures, or simpler tasks like data assembly, moderate
data processing etc);
  3. prefers to rely on SAS.
It is impossible; this kind of person does not exist. In my view,
statement #3 negates statement #1, or #2, or both.

And no, the tools are not similar. The end _is_ the tool you use.

> -----Original Message-----
> From: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] On Behalf Of Frank E Harrell Jr
> Sent: Monday, January 07, 2008 7:31 PM
> To: John Sorkin
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] I need arguments pro-S-PLUS and against SAS...
>
> John Sorkin wrote:
> > Frank,
> > I believe you are proving my point. The difference is not
> so much the language as the end users. I use SAS, R, and SPlus on a 
> regular basis. For some analyses, SAS is easiest to use, for some R 
> (or SPlus). I can be just as dangerous using SAS and I can be with R 
> if I don't think about what I am doing and not only check the 
> assumptions of my models, but also pay attention to the results of the

> checks. You see problems with SAS data sets because you know what to 
> look for and take the trouble to look for problems. When R (or SPlus) 
> becomes commonly used by the great unwashed public, the number of 
> poorly done analyses in these languages will increase. The basic 
> problem with statistical software is that by making analyses easy to 
> do, they allow anyone to do analyses. When an unprepared person sets 
> about doing a complex task that should demand proper training and 
> experience bad things happen quickly, and with high probability.
> >
> > In any event, regardless of which side of the argument
> members of the R listserver might take, we are all deeply in your debt

> for the many contributions you have made not only to the R 
> environment, but also to the R listserver. On behalf of the entire R 
> community, thank you.
> >
>
> We'll have to have a friendly but strong disagreement about this.  
> I've watched statisticians work too many times to not believe that 
> many will take the expedient route (e.g., assume linearity) when using

> non-flexible or non-powerful software (e.g., SAS).  And I don't find 
> errors in the data usually because I know the data.  I find errors 
> because I can say things like
>
>   library(Hmisc)
>   datadensity(mydata)   # show all raw data in small rug plots
>   hist.data.frame(mydata)  # postage-stamp size histograms of all 
> variables in dataset
>   latex(describe(mydata)) # like PROC UNIVARIATE but shows MUCH more 
> information in MUCH less space, including a high-resolution histogram 
> next to the tabular info for each variable
>
> I do agree with your comment about making things easy to do.
>
> > With greatest respect and thanks,
>
> Thanks very much for the kind words John.
>
> Cheers
>
> Frank
>
> > John
> >
> > John Sorkin M.D., Ph.D.
> > Chief, Biostatistics and Informatics University of Maryland School 
> > of Medicine Division of Gerontology Baltimore VA Medical Center 10 
> > North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524
> > (Phone) 410-605-7119
> > (Fax) 410-605-7913 (Please call phone number above prior to faxing)
> >
> >>>> Frank E Harrell Jr <f.harrell at vanderbilt.edu> 1/7/2008
> 6:41 PM >>>
> > John Sorkin wrote:
> >> I fear I risk being viewed as something of a curmudgeon,
> but the truth must be stated. S-Plus, R, SAS, etc. are all similar in 
> that they are all tools to an end and not an end in themselves. Any 
> one of the three can do most statistical analyses one might want to 
> do. I could point out the strengths of  any one of the programming 
> environments, but to be fair I would then be required to point out 
> each platform's weaknesses. In the end, what matters is the quality 
> and abilities of the person who uses the tools, not the tools 
> themselves. I don't think you can make a fair statement that any one 
> is absolutely better than the other.
> >> John
> >
> > John - I must respectfully disagree at least in part.  I
> have noticed
> > that SAS users are far more likely to assume linearity in doing 
> > regression modeling, because SAS makes it so difficult to
> specify that
> > you want an unknown smooth function of a covariate in a model.  SAS 
> > users are also less likely to bootstrap and to validate statistical 
> > models because it's such a pain to do those in SAS.  Also
> when I get SAS
> > datasets from companies that have paid a fortune to a
> SAS-based contract
> > research organization, I can quickly spot major data errors using S 
> > graphics; these errors were missed by all the SAS users
> because of poor
> > graphics.
> >
> > Frank
> >
> >> John Sorkin M.D., Ph.D.
> >> Chief, Biostatistics and Informatics University of Maryland School 
> >> of Medicine Division of Gerontology Baltimore VA Medical Center 10 
> >> North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524
> >> (Phone) 410-605-7119
> >> (Fax) 410-605-7913 (Please call phone number above prior to faxing)
> >>
> >>>>> Jeffrey J. Hallman <jhallman at frb.gov> 1/7/2008 4:09 PM >>>
> >> SAS programming is easy if everything you want to do fits
> easily into the
> >> row-at-a-time DATA step paradigm.  If it doesn't, you have
> to write macros,
> >> which are an abomination.  DATA step statements and macros
> are entirely
> >> different programming languages, with one doing
> evaluations at "compile" time,
> >> and the other at "run" time.  Except that that's not
> really true, either,
> >> witness the 'call symput()' construct.
> >>
> >> Then, if you want to interact at all with the user, you
> need to learn SCL, a
> >> third language, with it's own rules.  And to do anything
> sophisticated with a
> >> user interface (which will still look like hell), you have
> to learn the SAS
> >> A/F toolkit built on SCL.  And of course, A/F requires you to think

> >> differently yet again.
> >>
> >> So, to be a competent and versatile SAS programmer, you
> have to learn four
> >> languages and four paradigms, and keep them all straight
> in your head while
> >> programming.  Of course, hardly anyone can do this, so you
> usually find stacks
> >> of reference documentation close at hand when you visit a
> SAS programmer's
> >> office.
> >>
> >> R and Splus don't offer much in the way of GUI
> programming, but for problems
> >> that don't require a lot of GUI, it's very nice.  You
> learn one language, it's
> >> quite forgiving, it's interpreted and usually easy to
> debug, and the programs
> >> you end up with are far more readable and maintainable
> than anything a SAS
> >> programmer can turn out.  Reading my own SAS code is bad,
> and reading someone
> >> else's is torture.
> >>
> >> Do I sound like an R bigot?  Actually, I'm a Smalltalk
> bigot, which is even
> >> nicer than R.  But R is quite usable for most things I do,
> and I use Smalltalk
> >> for GUI-intensive stuff.  Speaking as a programmer, SAS is awful.
> >>
> >
> >
>
>
> --
> Frank E Harrell Jr   Professor and Chair           School of Medicine
>                       Department of Biostatistics Vanderbilt 
> University
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.