I can't resist dipping my oar in here:
For me, some significant advantages of SAS are
- Ability to input data in almost *any* conceivable form using the combination of features available through
input/infile statements, SAS informats and formats, data step programming, etc. Dataset manipulation
(merge, join, stack, subset, summarize, etc.) also favors SAS in more complex cases, IMHO.
I respectfully disagree Michael, in cases where the file sizes are not enormous. And in many cases repetitive SAS data manipulation can be done much easier using vectors (e.g., vectors of recodes) and matrices in R, as shown in the examples in Alzola & Harrell (http://biostat.mc.vanderbilt.edu/twiki/pub/Main/RS/sintro.pdf).
We are working on a project in which a client sends us 50 SAS datasets. Not only can we do all the complex data manipulations needed in R, but we can treat the 50 datasets as a array (actually a list( )) to handle repetitive operations over many datasets.
- Output delivery system (ODS): *Every* piece of SAS output is an output object that can be captured as
a dataset, rendered in RTF, LaTeX, HTML, PDF, etc. with a relatively simple mechanism (including graphs)
ods pdf file='mystuff.pdf'';
<< any sas stuff>>
ods pdf close;
- If you think the output tables are ugly, it is not difficult to define a template for *any* output to display
it the way you like.
I would like to see SAS ODS duplicate Table 10 in http://biostat.mc.vanderbilt.edu/twiki/pub/Main/StatReport/summary.pdf
Cheers,
Frank
- ODS Graphics (new in SAS 9.1) will extend much of this so that statistical procedures will produce many
graphics themselves with ease.
One significant disadvantage for me is the difficulty of composing multipanel graphic displays
(trellis graphics, linked micromaps, etc.) due to the lack of an overall, top-down graphics environment.
As well, there are a variety of kinds of graphics I've found extraordinarily frustrating to try to do
in SAS because of lack of coherence or generality in the output available from procedures --- an
example would be effect displays, such as implemented in R in the effects package. I can't agree, however, with Frank Harrell that SAS produces 'the worst graphics in the statistical software world.'
One can get ugly graphs in R almost as easily in SAS just by accepting the 80-20 rule: You can typically get 80% of
what you want with 20% of the effort. To get what you really want takes the remaining 80% of effort.
On the other hand, the active hard work of many R developers has led to R graphics for which the *default*
results for many graphs avoid many of the egregious design errors introduced in SAS in the days of pen-plotters
(+ signs for points, cross-hatching for area fill).
-Michael
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
