|Date: ||Sat, 7 May 2011 13:59:17 -0400|
|Reply-To: ||Vincent Granville <vincentg@DATASHAPING.COM>|
|Sender: ||"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>|
|From: ||Vincent Granville <vincentg@DATASHAPING.COM>|
|Subject: ||Why still use SAS with a lot of open source applications?|
This discussion was posted on our LinkedIn group. Here's my answer:
SAS has some nice features, such as the SQL procedure or simple "group by"
features. Try to compute correlations "by group" in R: say you have 2,000
groups, 2 variables e.g. salary and education level, and 2 million
observations - you want to compute correlation between salary and education
within each group.
It is not obvious, your best bet is to use some R package (see sample code on
Analyticbridge to do it), and the solution is painful, you can not return both
correlation and stdev "by group", as the function can return only one
argument, not a vector. So if you want to return not just two, but say 100
metrics, it becomes a nightmare.
Read discussion at http://bit.ly/jRJQvj