From: Frank E Harrell Jr <[EMAIL PROTECTED]> > per year in SAS licenses and have to hire armies of non-intellectually > challenged SAS programmers to do the work of significantly fewer > programmers that use modern statistical computing tools like R and S-Plus, > it is surprising that SAS is still the most commonly used tool in the > clinical side of drug development. I quit using SAS in 1991 because my > productivity jumped at least 20% within one month of using S-Plus.
I have not used SAS for even longer than you but to give SAS its due: - its pretty easy to produce all the info you need for a complete analysis with a few SAS commands. It would be possible to create analogous R commands but as it stands you have to keep going back and forth with R rather than just get it all out at once like you can with SAS. - SAS has more functionality in missing values. You can have different types of SAS missing values but in R you can have only one type of missing value. - the BY phrase in SAS is incredibly powerful and handy. You can get the same effect in R but I think that specific functionality is easier with SAS. Obviously R is incredibly powerful and functional and I really am out of touch with the SAS world but I thought I would make whatever case I could. I am willing to be corrected by those more in the know with SAS if this wrong. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help