From the menu click View and the click project then you will be able to see the your project with all your programs or open data sets ... View more

Hi Pihu I cleared base SAS certification exam and then I worked in Clinical trial area and I did not have any problem. Thereis a book on SAS Clinical trials available online. If you are already working in this area then you should be alright. Thanks Mit ... View more

Thanks Tom. ... View more

Please refer to 25027 - Compute the moving average of a variable There are codes with examples ... View more

Thanks Tom. Yes to create csv using Proc Export I believe you can send upto 2GB data. LRECL is for number of records? My number of recors is max of 5000 lines Regards, Mit ... View more

Hi Tom I use proc export as well to get a csv data. But sometimes I don't get to see all the columns exported. There are not too many rows though. I have about 3000 columns. Do you think the data step would help to sort my problem as well? Thanks Mit ... View more

Hi Could you please explain a bit more like what you have and what you would like to get? You can chnage the length. But it looks like your column1 (numeric part)) are same as the numeric part of column2. Do you like to match on these? Here is a suggestion: create a column (say match_col) as the numeric part from Column1 create a column(same name match_col) as the numeric part from Column2 then match the tables on match_col Thanks Mita ... View more

I mean all non missing the following procedure will replace all  missing numeric variable values with zero. proc stdize data= have reponly MISSING=0 out=want; var _numeric_; run;   ... View more

Hi Nikknock The following code works for me. DATA INDATA; INPUT VAR1 $ VAR2 $ VAR3 $; DATALINES; Yes No Maybe No Yes Maybe No No Yes ; RUN; data indata; set indata; id=_n_; run; proc sort data=indata; by id; run; proc transpose data=indata out=outdata; by id; var VAR1   VAR2   VAR3  ; run; data outdata; set outdata; count=1; drop id; rename _name_=VAR; run; proc sort data=outdata; by VAR col1; ; run; proc summary data=outdata ; by VAR col1; var count; output out=want (drop=_:)sum=; run; and the output is VAR COL1 count VAR1 No 2 VAR1 Yes 1 VAR2 No 2 VAR2 Yes 1 VAR3 Maybe 2 VAR3 Yes 1 ... View more

Hi zqkal I think the following paper will help you. http://www.lexjansen.com/pharmasug/2010/sas/sas-hw-sas01.pdf Goodluck Mit ... View more

%ler var=var1 var2 var3;  *list the variables in the order you would like to. Data want; retain &varlist.; set data have; keep &varlist.; run; ... View more

the following procedure will replace all  numeric variable values with zero. proc stdize data= have reponly MISSING=0 out=want; var _numeric_; run; ... View more

How about the following code data have ; set have; count=1; run; proc sort data=have; by PAT    ENC   ADMIT  ; run; proc summary data=have missing nway; by PAT    ENC   ADMIT  ; var EM    IP   OP count; output out=want(drop=_:)  sum=; run; data want; set want; format result $20.;      if EM=1 then do;           if IP=1 and OP=0 then result='EM to IP';           else if IP=1 and OP=1 then result='IP to OP';           else if IP=0  and OP=1 then result='EM to OP';           else if IP=0  and OP=0 then result='EM to DISCHARGE';      end; run; proc sort data=want out=want1(keep=PAT    ENC   ADMIT  result); by PAT    ENC   ADMIT ; run; data final; merge have(in=a) want1(in=b);      by PAT    ENC   ADMIT ;      if a; run; ... View more