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SAS or R software

3 messages · BXC (Bendix Carstensen), Frank E Harrell Jr, Thomas Friedrichsmeier

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Two major advantages of SAS that seems to have been overlooked in
the previous replies are:

1) The data-set language is SAS for data manipulation is more
   human-readable than R-code in general. 
   R is not a definite write-only laguage as APL, but in particular
   in datamanipulation it is easy to write code that is impossible
   to decipher after few weeks. 
   You can also produce unreadable code in SAS, but it generally takes 
   more of an effort.

   Thus: Data manupulation is easier to document in SAS than in R.

2) proc tabulate.
   This procedure enables you to do extensive sensible tabulation
   of your data if you are prepared to read the manual.
   (This is not a product of the complexity of the software,
    but of the complexity of the tabulation features).
   Compared to this only rudimentay tools exist in R (afaik).

So if you want to do well documented data manipulation and clear
and compact tables go for SAS.

If you want to do statistical analyses and graphics (in finite time)
go for R.

Bendix Carstensen
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Bendix Carstensen
Senior Statistician
Steno Diabetes Center
Niels Steensens Vej 2
DK-2820 Gentofte
Denmark
tel: +45 44 43 87 38
mob: +45 30 75 87 38
fax: +45 44 43 07 06
bxc at steno.dk
www.biostat.ku.dk/~bxc
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BXC (Bendix Carstensen) wrote:
I agree with the readability of data manipulation code, especially for 
novice users.  As far as functionality for data manipulation is 
concerned, R has more flexibility and is faster to program once one has 
experience.  I do think that learning data manipulation techniques in R 
takes a while.
I could not disagree more with that statement.  Look for example at 
http://biostat.mc.vanderbilt.edu/twiki/pub/Main/StatReport/summary.pdf . 
  With R you can customize tables by specifying your own function for 
computing any statistic of interest.  Let's see how to use PROC TABULATE 
to display stratified Kaplan-Meier 4-year survival estimates along with 
median and median life length, not to mention match the fine control of 
formatting available using the combination of R and LaTeX.
Readability is different from being well-documented.  And for clear and 
compact tables, R is the winner hands down.

Frank Harrell

  
    
#
Hello,

BXC (Bendix Carstensen) schrieb:
Not quite sure if this is a valid point! Mostly you'll have to comment 
on code as it is taught in programming course.
If your comments are clear, there shouldn't be any problems to 
understand your code after weeks , month or maybe...........


Thomas