Frank,
I can't see the code you mention - Web marshall at work - but I don't think
you should be too quick to run down SAS - it's a powerful and flexible
language but unfortunately very expensive.
Your example mentions doing a vector product in the macro language - this
only suggest to me that those people writing the code need a crash course
in SAS/IML (the matrix language). SAS is designed to work on records and so
is inapproprorriate for matrices - macros are only an efficient code
copying device. Doing matrix computations in this way is pretty mad and the
code would be impossible never mind the memory problems.
SAS recognise that but a lot of SAS users remain familiar with IML.
In IML by contrast there are inner, cross and outer products and a raft of
other useful methods for matrix work that R users would be familiar with.
OLS for example is one line:
b = solve(X`X, X`y) ;
rss = sqrt(ssq(y - Xb)) ;
And to give you a flavour of IML's capabilities I implemented a SAS version
of the MARS program in it about 6 or 7 years ago.
BTW SPSS also has a matrix language.
Gerard
Frank E Harrell
Jr
<f.harr...@vander To
bilt.edu> R list <r-h...@stat.math.ethz.ch>
Sent by: cc
r-help-boun...@r-
project.org Subject
[R] Inefficiency of SAS Programming
26/02/2009 22:57
If anyone wants to see a prime example of how inefficient it is to
program in SAS, take a look at the SAS programs provided by the US
Agency for Healthcare Research and Quality for risk adjusting and
reporting for hospital outcomes at
http://www.qualityindicators.ahrq.gov/software.htm . The PSSASP3.SAS
program is a prime example. Look at how you do a vector product in the
SAS macro language to evaluate predictions from a logistic regression
model. I estimate that using R would easily cut the programming time of
this set of programs by a factor of 4.
Frank
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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