Please do not post the same question multiple times. ... View more

Please do not post the same question multiple times. ... View more

Simple enough with an array. But the input variable name should not be one of the target variable names, that just complicates things. data have; input X; datalines; 71 122 167 122 194 166 167 266 365 ; So read 3 observations at a time and insert them into the proper variable using an index into an array. data want; array p p1-p3; do column=1 to 3 until(eof); set have end=eof; p[column]=x; end; drop column x; run; If you are actually reading the data from a text file then just read it originally directly into the array. data want; input p1-p3; datalines; 71 122 167 122 194 166 167 266 365 ; ... View more

I don't see one model as being preferable over the other but rather as the two models answering different questions. If your interest is in modeling the time to the event, then use the survival model and your censored data. If the interest is in modeling the probability of the event occurring within six months, then use the logistic model and those that don't experience the event are simply nonevent observations to be used along with the event observations. ... View more

I hate that.  So somebody got a homework assignment or a job contract someplace and posted the same issue multiple times.  I think I'll delete my response.    ... View more

I would argue you actually don't want your data in your binary column arrangement. Add a new drug and you have to add a new column.      I would argue more normalized data like:   ID Drug Date or dosage or whatever 1 Ceftazidme   1 Ciprofloxacin   2 Ceftazidme   2 Colistin   2 Vancomycin   3 Cefazolin   3 Ceftazidme   3 Meropenem   4 Minocycline   4 Colistin     which is essentially the format of the TEMP table in the @PeterClemmensen code would you do you more favors in the long run in terms of querying.    proc sql; select drug, count(id) as "Number of IDs Taking Drug"n from temp group by drug; quit; drug Number of IDs Taking Drug Cefazolin 1 Cefepime 1 Ceftazidme 3 Ciprofloxacin 1 Colistin 2 Meropenem 1 Minocycline 1 Vancomycin 1 ... View more

What does "finer output" mean for this? ... View more

Thanks HB. However I have to do this in VA. Incidentally I did figure it out. The solution is in another post here:   https://communities.sas.com/t5/SAS-Visual-Analytics/SAS-VA-how-to-create-calculations-using-columns-data-in-a-List/m-p/827813/highlight/false#M16325 ... View more

data have; input recip_id Dose1 (admin_date CVX MC Auth Lot_id dose_num vax_fund admin_state interval) (:$40.); Datalines; 1 1 10/16/2021 208 PF US acvds 1 k MI . 1 2 11/6/2021 208 PF US bdsa 2 k MI 21 1 3 5/29/2021 207 MO US bde1de 3 k MI 90 2 1 6/7/2021 207 MO US 2ds42 1 h OH . 3 1 7/7/2021 208 PF US 3fs1 1 h WI . 3 2 7/7/2021 208 PF US fews2 2 k WI 28 3 3 8/4/2021 208 PF US gesw21 3 k WI 87 4 1 1/21/2022 208 PF US fewq21 1 h NY . 4 2 12/22/2020 208 PF US gresa21 2 h NY 28 5 1 1/12/2021 212 JS US gewa2 1 k WV . 6 1 4/12/2021 207 MO US fewqa2 1 k IN . 6 2 4/29/2021 207 MO US gewad2 2 k IN 27 ; run; proc sql noprint; select distinct catt('have(where=(Dose1=',Dose1,') rename=( admin_date=admin_date',Dose1,' CVX=CVX',Dose1,' MC=MC',Dose1, ' Auth=Auth',Dose1,' Lot_id=Lot_id',Lot_id,' dose_num=dose_num',Dose1, ' vax_fund=vax_fund',Dose1,' admin_state=admin_state',Dose1,' interval=interval',Dose1,' ))') into :merge separated by ' ' from have; quit; data want; merge &merge.; by recip_id; drop Dose1; run; ... View more

So 78 splits ... the user then has to find the one they want, let's say John August. in that list of 78 ... or the user could have one Excel file and filter in Excel for John & August   Roughly equal in amount of effort for the end user, in my opinion   Tomato ... tomahhto   But lots more effort for the programmer. ... View more

In many languages/programs, either double and single quotes can be used interchangeably, so as a solution double quotes didn't jump off the screen at me. I appreciated the response that actually solved my problem. ... View more

Thank you for your help. ... View more

Just another way -- data have; input ID DESC $2.; datalines; 1234 AB 5678 CD 5678 EF 9999 GH run; proc transpose data=have out=have_t(drop=_:); by id; var DESC; run; data want(drop=col:); set have_t; desc=catx("_", of col:); run; ... View more

You are still trying to cure symptoms instead of causes. How do your datasets originate? If you get them from somewhere else in the form of Excel spreadsheets (which is the worst file format for data transfer), you must fix that process. ... View more

You correct the source data wasn't correct, it was after I did proc transpose.  The bank data is set as id, product,  delq. Thank you for the help much appreciated.    I'm working with your solution now.   ... View more