Dear allstat,
I would like to thank all those who contributed to this interesting topic. Given the number of replies that I have had on the subject it is going to take a little time to collate them all. Once done, I will certainly post to the list as it gives some interesting pointers as to the merits, or otherwise, of the two packages.
Best regards
Mike Griffiths
Michael Griffiths, Ph.D.
Chemometrician
Training, Quality and Statistics Group
LGC Limited
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Middlesex, TW11 0LY, UK
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>>> Peter Flom <[log in to unmask]> 04/20/06 5:47 pm >>>
>>> Michael Griffiths <[log in to unmask]> 4/20/2006 9:34 >> wrote
<<<
This is a question of general interest really, I hear an awful lot about the SAS package. Indeed, when job adverts appear connected with clinical data analysis (CRO) this package is nearly always cited as a definite prerequisite. My question is this, If one were to compare R with SAS what would be the strengths and weaknesses of R compared to SAS, or the other way round if easier.
>>>
SAS is expensive, R is free.
SAS has wonderful tech support, R does not have any.
Both have excellent mailing lists, but the SAS list is more friendly to newbies.
The newest statistical techniques are implemented in R much sooner than in SAS.
SAS documentation is verbose, R documentation is terse.
R graphics are better, although SAS ODS graphics have narrowed the gap a bit.
I find SAS much easier to use for data manipulation, but part of this is because I am more used to it.
If you need to create novel methods or graphs, R is better.
SAS is more consistent, procedure to procedure, because it's written by one set of people in a central location.
R is open source, and you can modify the source code to suit your purposes.
I wouldn't want to give up either of them.
Peter
Peter L. Flom, PhD
Assistant Director, Statistics and Data Analysis Core
Center for Drug Use and HIV Research
National Development and Research Institutes
71 W. 23rd St
http://cduhr.ndri.org
www.peterflom.com
New York, NY 10010
(212) 845-4485 (voice)
(917) 438-0894 (fax)
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