@madpumpkinpie: Just wanted to point out a couple of things. First, I agree with @PaigeMiller, if you're doing the analysis to test hypotheses, the correct method is to use a single analysis.
However, so that you gain a better understanding of how SAS works, you could still get exactly what you asked for without having to "split" the data.
e.g., @PaigeMiller recommended:
proc glm data=have;
class weight treatment;
model kcal=weight|treatment;
run;
To do the same thing, separately for each level of treatment, one could use:
proc sort data=have;
by treatment;
run;
proc glm data=have;
class weight;
by treatment;
model kcal=weight;
run;
@novinosrin: While splitting the data isn't needed to solve the problem, this question was cross-posted on SAS-L @SAShole (i.e., Paul Dorfman) pointed out that no sort is needed when using the hash object to split such a file. I ran a test comparing your method with the one that Paul suggested, and I totally have to agree with him. He suggested:
data _null_ ;
dcl hash x() ;
x.defineKey ('weight') ;
x.defineData ('weight','h') ;
x.defineDone () ;
dcl hash h ;
do until (z) ;
set have end = z ;
if x.find() ne 0 then do ;
h = _new_ hash (dataset:'have(obs=0)', multidata:'y') ;
h.defineKey ('weight') ;
h.defineData (all:'y') ;
h.defineDone () ;
x.add() ;
end ;
h.add() ;
end ;
dcl hiter i('x') ;
do while (i.next()=0) ;
h.output (dataset: weight) ;
end ;
stop ;
run ;
Your solution would only be (very) slightly faster IF the data were already sorted.
Art, CEO, AnalystFinder.com
