>>> "Rau, Roland" <[EMAIL PROTECTED]> >>> wrote <<< IMO this is a very good proposal but I think that the main problem is not the "translation" of one function in SPSS/Stata/SAS to the equivalent in R. Remembering my first contact with R after using SPSS for some years (and having some experience with Stata and SAS) was that your mental framework is different. You think in "SPSS-terms" (i.e. you expect that data are automatically a rectangular matrix, functions operate on columns of this matrix, you have always only one dataset available, ...). This is why "jumping" from SPSS to Stata is relatively easy. But to jump from any of the three to R is much more difficult. This mental barrier is also the main obstacle for me now when I try to encourage the use of R to other people who have a similar background as I had. What can be done about it? I guess the only answer is investing time from the user which implies that R will probably never become the language of choice for "casual users". But popularity is probably not the main goal of the R-Project (it would be rather a nice side-effect). >>>>
As someone who uses SAS qutie a bit and R somewhat less, I think Roland makes some excellent points. Going from SPSS to SAS (which I once did) is like going from Spansih to French. Going from SAS to R (which I am trying to do) is like going from English to Chinese. But it's more than that. Beyond the obvious differences in the languages is a difference in how they are written about; and how they are improved. SAS documentation is much lengthier than R's. Some people like the terseness of R's help. Some like the verboseness of SAS's. SOme of this difference is doubtless due to the fact that SAS is commercial, and pays people to write the documentation. I have tremednous appreciation for the unpaid effort that goes into R, and nothing I say here should be seen as detracting from that. As to how they are improved, the fact that R is extended (in part) by packages written by many many different people is good, becuase it means that the latest techniques can be written up, often by the people who invent the techniques (and, again, I appreciate this tremendously), but it does mean that a) It is hard to know what is out there at any given time; b) the styles of pacakages difer somewhat. In addition, I think the distinction between 'casual user' and serious user is something of a false dichotomy. It's really a continuum, or, probably, several continua, that make R harder or easier for people to learn. I like R. I like it a lot. I like that it's free. I like that it's cutting edge. I like that it can do amazing graphics. I like that the code is open. I like that I can write my own functions in the same language. And, again, I am amazed at the amount of time and effort people put into it. But I do think that the link in the original post made some good points, and the writer of that post is not the only one who has found R difficult to learn. Peter ______________________________________________ [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
