hi ,,, another idea ... data want; length col2 col3 $6; set have; col2 = catq('2a',col1); col3 = catq('1a',col1); run; or, no LENGTH statement needed ... data want; set have; col2 = put(col1,quote.); col3 = translate(col2,"'",'"'); run; ... View more

hi ... one other suggestion is to use a temporary array (values retained, no extra variables) ... data rollsums; array vv(3) _temporary_; set test; if _n_ ge 3 then rollsum = sum(of vv(*)); vv(mod(_n_-1,3) + 1 ) = value; run; ... View more

hi ... Ksharp's neat solution has been much discussed on SAS-L for some more reading ... http://listserv.uga.edu/cgi-bin/wa?A2=ind0804B&L=sas-l&D=0&P=29162 ... View more

hi ... one idea on what happens ...  if you do this (similar to your job)... proc summary data=sashelp.class nway; class age sex; var height; output out=stats (drop=_:)  n=n mean=mean std=std var=var; format mean 10.1; run; proc transpose data=stats out=tstats name=statistic; by age; id sex; var mean std var; run; you are putting all the calculated statistics into two variables, F and M (the two values of the ID variable in transpose)  and are combining a formatted MEAN with unformatted STD and VAR (from the VAR statement) ... data set TSTATS ...        Alphabetic List of Variables and Attributes #    Variable     Type    Len    Label 1    Age          Num       8 3    F            Num       8 4    M            Num       8 2    statistic    Char      8    NAME OF FORMER VARIABLE if you change the FORMAT statement in PROC SUMMARY (format all the statistics) ... format mean std var 10.1; after the same transpose, you'll see ..             Alphabetic List of Variables and Attributes #    Variable     Type    Len    Format    Label 1    Age          Num       8 3    F            Num       8    F10.1 4    M            Num       8    F10.1 2    statistic    Char      8              NAME OF FORMER VARIABLE and ... Age    statistic            F             M 11     n                  1.0           1.0 11     mean              51.3          57.5 11     std                 .             . 11     var                 .             . 11     median            51.3          57.5 12     n                  2.0           3.0 12     mean              58.1          60.4 12     std                2.5           3.9 12     var                6.1          15.5 12     median            58.1          59.0 <more> so, if you format all the statistics in your PROC MEANS, the format should be retained for the variables created by transpose (though you'll have N with a decimal place that's not needed) format n mean std median min max 6.1; a suggestion ... since you want to transpose by visit cpevent, how about using a CLASS statement to create a data set that is in the correct order for transpose without having to do that intermediate  sort ... proc summary data=newss nway; var vsbasech; class visit cpevent vstext treattxt; output out=newssmed (drop=_:) n=n mean=mean std=std median=median min=min max=max; format n mean std median min max 6.1; run; proc transpose data=newssmeds out=newssmedst (drop=_label_) name=statistic; by visit cpevent; id vstext treattxt; var n mean std median min max; run; ... View more

hi ... more reading material about _INFILE_ ... Now _INFILE_ is an Automatic Variable − So What? Howard Schreier http://www.nesug.org/proceedings/nesug01/cc/cc4018bw.pdf More _Infile_ Magic Peter Crawford http://www2.sas.com/proceedings/sugi28/086-28.pdf I haven't seen any equivalent papers on _FILE_, only postings on SAS-L and here on COMMUNITIES ... View more

hi ... you are better off looking at Peter's answer in that you need that @ sign to keep the results in the buffer the problem is (as Peter stated) the meaning of OBS ... you asked for two observations, not 1 ... View more