[EMAIL PROTECTED] wrote: > Thank you to all those that responded to Delphine's original post on R and > clinical studies. They have provided much food for thought. > > I had a couple of follow up questions/comments. Andrew is very correct in > pointing out that there are classes and workshops available for R. It's my > understanding that there are even commercial versions of R that now provide > formal commercial-style courses. And at any rate, the money saved by > potentially avoiding pricey software could certainly justify any training > expense in time or money - this assumes of course that the pricey software > could be dispensed with (I suspect that would take considerable time at my > current company as so many legacy projects have been done in proprietary > software). I still think that R provides less 'hand-holding' and requires > more initiative (which may be more or less present on a per > programmer/statistician basis). > > I guess one could always integrate R/Splus in with SAS, as Terry's group > has done at Mayo - I will probably do this at least as a start. I have a > few concerns with regards to this approach (these may be needless concerns, > but I will venture expressing them anyway). First, I'm worried about the > possibility of compatability concerns (will anyone be worried about a SAS > dataset read into R or vice-versa?). Second, I would prefer focusing all > my learning on one package if possible. I actually have more experience > with SAS (as do others in my group), and if the switch to R is to be made I > would like to make that switch as complete as possible. This would also > avoid requiring new hires to know both languages. Third, if SAS is to be > kept around, it defeats one of the main advantages of having open source > code in the first place (R is wonderfully free!). Like Mayo, Baylor Health > (my previous employer) used both Splus and SAS. I was warned that data > manipulation would be much more difficult in R/Splus than it was in SAS. > To be honest, and I say this humbly realizing that most posters to this > list have much more experience than I, I haven't found data manipulation to > be that much more difficult in R/Splus (at least as I have gained > experience in R/Splus). I can think of two exceptions (1) large datasets > and (2) SAS seems to play nicer with MS products (e.g. PROC IMPORT seemed > to read in messy Excel spreadsheets better than importData in Splus). Is > it possible (and I again say this with MUCH humility) that the perceived > advantages of SAS with regards to data manipulation may be due in part to > some users only using R/Splus for stat modeling and graphics (thus never > becoming familiar with the data manipulation capabilities of R/Splus) or to > the reluctance of SAS-trained individuals and companies to make the > complete switch?
You are exactly correct on this point. Some graduate programs only teach students how to use R/S-Plus for modeling and graphics. R/S-Plus are wonderful for data manipulation - more powerful than SAS but not easy to learn (plus in R there are sometimes too many ways to do something; new users get lost - e.g. the reshape and reShape functions and the reshape package). http://biostat.mc.vanderbilt.edu/twiki/pub/Main/RS/sintro.pdf has many examples of complex data manipulation as do some web sites. We do analysis for pharmaceutical companies with 100% of the data manipulation done in R after importing say 50 SAS datasets into R. Doing tasks such as finding a lab value measured the closest in time to some event is much more elegant in R/S-Plus than in SAS. Frank > > Tony, the story about the "famous software" and the "certain operating > system" at the "large company" was priceless. > > In closing, I should mention that in all posts I am speaking for myself and > not for Edwards LifeSciences. > > Regards, > -Cody > > ______________________________________________ > [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 > and provide commented, minimal, self-contained, reproducible code. > -- 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 and provide commented, minimal, self-contained, reproducible code.
