I think part of the whole issue here is the nature of
R vs. a system like
SPSS or what have you. There are many differences - and many favor
R. One key difference is that
R is free. That means that the people who develop it are not paid to do so. So, while many of them try to be very helpful, they are writing packages because they think it's fun (or, in some cases, because it helps their careers - publish or perish).
SAS costs a great deal of money.
One thing you get for that money is people who are paid to do things, including things that are boring. So, for example, in the SAS documentation for most statistical PROCs there is an extensive section on comparisons with other PROCs. In addition, the SAS documentation has big sections on statistics (as opposed to the PROCs), the documentation lists many references, has many fully worked and annotated examples etc.
For example, if you type ?lm you get something that, if printed out, might be 5 pages or so (at a guess). The SAS documentation for PROC GLM (the rough equivalent) is well over 100 pages. The example at the end of ?lm is 12 lines long (admittedly, there are more complex examples elsewhere). The first example in PROC GLM is about 10 pages.
In addition, and compounding the above, is that
R documentation almost prides itself on its terseness; while
SAS documentation prides itself on verbosity and completeness.
I like both
R. But they are very different in many ways, including what you can expect of the people who develop the packages; indeed, at
SAS the people who develop the PROCs are usually not the people who write the DOCs; and they certainly aren't the people who answer the help lines. OTOH, here, you asked a question about
rms and you got an answer from Frank Harrell; and you got it promptly, too.