[R] things that are difficult/impossible to do in SAS or SPSSbut simple in R

Frank E Harrell Jr f.harrell at vanderbilt.edu
Thu Jan 17 14:33:35 CET 2008


Walter Paczkowski wrote:
> Good morning,
> 
> I use SAS and R/S-Plus as my primary tools so I have a lot of experience with these programs.  By far and away, SAS is superior for handling the "messy" datasets, but also the very large ones.  I work at times with datasets in the hundreds of thousands (and on occasion, millions) of records.  SAS, and especially PROC SQL, are invaluable for this.  But once I get to datasets manageable for R/S-Plus, then I ship to these tools for the programming and graphics.  This seems to work great.
> 
> Walt Paczkowski
> Data Analytics Corp.

Previously I used SAS for 23 years and now R/S-Plus for 17.  SAS is 
effective for large datasets (in my work > 500,000 subjects) but except 
for that, R is far superior to SAS for data management and manipulation. 
  Just four of the reasons are that you can

- merge data frames multiple ways and compare the results
- deal with arrays (lists) of datasets using high-level operators
- easily do complex calculations on serial data such as find the highest 
blood pressure per subject that is measured before something else is 
measured
- sense the type of a variable (character, factor, date, discrete 
numeric, continuous numeric, etc.) while analyzing it, and tailor the 
analysis to the type of variable

http://biostat.mc.vanderbilt.edu/twiki/pub/Main/RS/sintro.pdf has a 
large section on data manipulation in S.

Frank

> 
> 
> -----Original Message-----
>> From: Rob Robinson <rob.robinson at bto.org>
>> Sent: Jan 17, 2008 4:31 AM
>> To: r-help at stat.math.ethz.ch
>> Subject: Re: [R] things that are difficult/impossible to do in SAS or	SPSSbut simple in R
>>
>>
>> I wonder if those who complain about SAS as a programming environment have
>> discovered SAS/IML which provides a programming environment akin to Matlab
>> which is more than capable (at least for those problems which can be treated
>> with a matrix like approach). As someone who uses both SAS and R - graphical
>> output is so much easier in R, but for handling large 'messy' datasets SAS
>> wins hands down...
>> Cheers
>> Rob
>>
>> *** Want to know about Britain's birds? Try  www.bto.org/birdfacts ***
>>
>> Dr Rob Robinson, Senior Population Biologist
>> British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
>> Ph: +44 (0)1842 750050         E: rob.robinson at bto.org
>> Fx: +44 (0)1842 750030         W: http://www.bto.org
>>
>> ==== "How can anyone be enlightened, when truth is so poorly lit" =====
>>  
>>
>>> -----Original Message-----
>>> From: r-help-bounces at r-project.org 
>>> [mailto:r-help-bounces at r-project.org] On Behalf Of Jeffrey J. Hallman
>>> Sent: 16 January 2008 22:38
>>> To: r-help at stat.math.ethz.ch
>>> Subject: Re: [R] things that are difficult/impossible to do 
>>> in SAS or SPSSbut simple in R
>>>
>>> SAS has no facilities for date arithmetic and no easy way to 
>>> build it yourself.  In fact, that's the biggest problem with 
>>> SAS: it stinks as a programming environment, so it's always 
>>> much more difficult than it should be to do something new.  
>>> As soon as you get away from the canned procs and have to 
>>> write something of your own, SAS falls down.
>>>
>>> I don't know enough about SPSS to comment.
>>> --
>>> Jeff




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