A few thoughts about R vs SAS:
I started learning SAS 8 years ago at IBM, I believe it was version 6.10.
I started with R 7 months ago.
Learning curve:
I think I can do everything in R after 7 months that I could do in SAS after
about 4 years.
Bugs:
I suffered through several SAS version changes, 7.0, 7.1, 7.2, 8.0, 9.0 (I
may have misquoted some version numbers). Every version change gave me
headaches, as every version release (of an expensive commercially produced
software set) had bugs which upset or crashed previously working code. I had
code which ran fine under Windows 2000 and terribly under Windows XP. Most bugs
I found were noted by SAS, but never fixed.
With R I have encounted very few bugs, except for an occasional crash of R,
which I usually ascribe to some bug in Windows XP.
Help:
SAS help was OK. As others have mentioned, there is too much. I even had the
set of printed manuals on my desk (stretching 4 feet or so), which were quote
impenetrable. I had almost no support from colleagues: even within IBM the
number of advanced SAS users was small.
With R this mailing list has been of great help: almost every issue I copy
some program and save it as a "R hint xxxx" file.
--> A REQUEST
I would say that I would appreciate a few more program examples with the help
pages for some functions. For instance, "?Control" tells me about "if(cond)
cons.expr else alt.expr", however an example of
if(i==1) { print("one")
} else if(i==2) { print("two")
} else if(i>2) { print("bigger than two") }
at the end of that help section would have been very helpful for me a few
months ago.
Functions:
Writing my own functions in SAS was by use of macros, and usually depended
heavily on macro substitution. Learning SAS's macro language, especially macro
substitution, was very difficult and it took me years to be able to write
complicated functions. Quite different situation in R. Some functions I have
written by dint of copying code from other people's packages, which has been
very helpful.
I wanted to generate arbitrary k-values (the k-multiplier of sigma for a
given alpha, beta, and N to establish confidence limits around a mean for small
populations). I had a table from a years old microfiche book giving values but
wanted to generate my own. I had to find the correct integrals to approximate
the k-values and then write two SAS macros which iterated to the desired level
of tolerance to generate values. I would guess that there is either an R base
function or a package which will do this for me (when I need to start
generating AQL tables). Given the utility of these numbers, I was disappointed
with SAS.
Data manipulation:
All SAS data is in 2-dimensional datasets, which was very frustrating after
having used variables, arrays, and matrices in BASIC, APL, FORTRAN, C, Pascal,
and LabVIEW. SAS allows you to access only 1 row of a dataset at a time which
was terribly horribly incomprehensibly frustrating. There were so many many
problems I had to solve where I had to work around this SAS paradigm.
In R, I can access all the elements of a matrix/dataframe at once, and I can
use >2 dimensional matrices. In fact, the limitations of SAS I had ingrained
from 7.5 years has sometimes made me forget how I can do something so easily in
R, like be able to know when a value in a column of a dataframe changes:
DF$marker <- DF[1:(nrow(DF)-1),icol] != DF[2:nrow(DF),icol]
This was hard to do in SAS...and even after years it was sometimes buggy,
keeping variable values from previous iterations of a SAS program.
One very nice advantage with SAS is that after data is saved in libraries,
there is a GUI showing all the libraries and the datasets inside the libraries
with sizes and dates. While we can save Rdata objects in an external file, the
base package doesn't seem to have the same capabilities as SAS.
Graphics:
SAS graphics were quite mediocre, and generating customized labels was
cumbersome. Porting code from one Windows platform to another produced
unpredictable and sometimes unworkable results.
It has been easier in R: I anticipate that I will be able to port R Windows
code to *NIX and generate the same graphics.
Batch commands:
I am working on porting some of my R code to our *NIX server to generate
reports and graphs on a scheduled basis. Although a few at IBM did this with
SAS, I would have found doing this fairly daunting.
-Leif
-----------------------------
Leif Kirschenbaum, Ph.D.
Senior Yield Engineer
Reflectivity
[EMAIL PROTECTED]
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