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Inefficiency of SAS Programming

Ajay ohri wrote:
A system that requires Excel for its success is not a complete system.
Really?  Try this in SAS:

library(Design)
f <- lrm(death ~ rcs(age,5)*sex)
anova(f)     # get test of nonlinearity of interactions among other things
nomogram(f)  # depict model graphically

The restricted cubic spline in age, i.e., assuming the age relationship 
is smooth but not much else, is very easy to code in R.  There are many 
other automatic transformations available.  The lack of generality of 
the SAS language makes many SAS users assume linearity for more often 
than R users do.

Also note that PROC LOGISTIC, without invocation of a special option, 
would make the user believe that older subjects have lower chances of 
dying, as SAS by default takes the even being predicted to be death=0.

Frank