@tocilj    The double proc transpose is nice in that it has a simple structure, and it uses a pre-packaged sas routine.   But it may not scale well.  Transposing 1,000,000 observations will create a dataset with 1,000,000 variables in the intermediate data set TEST1.  The entire dataset would have to be processed two times, which can begin to use significant resources. ... View more

It depends partly on how you define your percentages but I'm a fan of the double proc freq for that type of work.  SQL with distinct works as well.   I illustrate both options here: https://github.com/statgeek/SAS-Tutorials/blob/master/count_distinct_by_group.sas   *Double PROC FREQ; proc freq data=sashelp.cars noprint; table origin * make / out=origin_make; run; proc freq data=origin_make noprint; table origin / out= distinct_freq; run; title 'PROC FREQ'; proc print data=distinct_freq; run; title 'PROC SQL'; proc print data=distinct_sql; run;     If you want the percentages in the output data set make sure to specify OUTPCT or OUTPERCENT (can't recall which is correct) to capture the percents.   ... View more

@pmpradhan wrote: I was thinking whether it is :   Procedure 1: proc means data=have; var pct_elderly; where x=1; run;   or  Procedure 2: data want; set have; high_elderly=(pct_elderly>=means+sd); run;   proc freq data=want; tables high_elderly; where x=1; run; Did you even try these? Do they produce the answer you want? If not, state clearly what is missing from these answers.   Specifically, what is wrong with your Procedure 1? It seems like it does what you are asking (although I'm not 100% clear on what you are asking) ... View more

@pmpradhan wrote: The logic in this particular case is to translate the stata code so that I can have same results. As I replied above, I'm few numbers far from getting an exact match. I will try with sorting the data again and update this thread. I appreciate the community support-here, Thanks team!  Quite often with non-trivial cases the "same results" may not be possible due to things like internal rounding of values, precision of the hardware/software used or just plain differences in algorithms for approximations.   If you search this forum you will find a few questions about people getting different results between SAS version X.X and Y.Y where algorithms are tweaked between versions, or moving from one OS to another, especially the 32 bit vs. 64 bit versions of the same OS.   You may have to set a target for "close enough". ... View more