[R] A comment about R:
flom at ndri.org
Tue Jan 3 12:27:39 CET 2006
>>> "Rau, Roland" <Rau at demogr.mpg.de> >>> 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
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
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.
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