[R] Inefficiency of SAS Programming

Frank E Harrell Jr f.harrell at vanderbilt.edu
Fri Feb 27 14:48:32 CET 2009


Wensui Liu wrote:
> Thanks for pointing me to the SAS code, Dr Harrell
> After reading codes, I have to say that the inefficiency is not
> related to SAS language itself but the SAS programmer. An experienced
> SAS programmer won't use much of hard-coding, very adhoc and difficult
> to maintain.
> I agree with you that in the SAS code, it is a little too much to
> evaluate predictions. such complex data step actually can be replaced
> by simpler iml code.

Agreed that the SAS code could have been much better.  I programmed in 
SAS for 23 years and would have done it much differently.  But you will 
find that the most elegant SAS program re-write will still be a far cry 
from the elegance of R.

Frank

> 
> On Thu, Feb 26, 2009 at 5:57 PM, Frank E Harrell Jr
> <f.harrell at vanderbilt.edu> wrote:
>> 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
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 
> 
> 


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



More information about the R-help mailing list