Inefficiency of SAS Programming

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of Gerard M. Keogh
Sent: Friday, February 27, 2009 7:19 AM
To: Frank E Harrell Jr
Cc: r-help-bounces at r-project.org; R list
Subject: Re: [R] Inefficiency of SAS Programming

Yes Frank, I accept your point but nevertheless IML is the proper place
for
matrix work in SAS - mixing macro-level logic and computation is
another
question - R is certainly more seemless in this respect.

Gerard



             Frank E Harrell
             Jr
             <f.harrell at vander
To
             bilt.edu>                 "Gerard M. Keogh"
                                       <GMKeogh at justice.ie>
             27/02/2009 13:55
cc
                                       R list <r-
help at stat.math.ethz.ch>,
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Subject
                                       Re: [R] Inefficiency of SAS
                                       Programming










Gerard M. Keogh wrote:

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

But try this:

PROC IML;
... some custom user code ...
... loop over j=1 to 10 ...
...   PROC GENMOD, output results back to IML
...

IML is only a partial solution since it is not integrated with the PROC
step.

Frank

             Frank E Harrell

             Jr

             <f.harrell at vander

To

             bilt.edu>                 R list <r-

help at stat.math.ethz.ch>

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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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--
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt
University