Hi all, I am seeking some help in converting a free text variable that contains multiple observations into a numeric variable while expanding to a long data set with potentially multiple rows per person.   Basically, in my "have" dataset, the AE_free_text includes codes for adverse events that were entered with codes in free text. When an individual had more than one adverse event at a study visit, the data entry person inputted this all on the same row. I want to have a long dataset so that each adverse event is on one line per participant.   Thank you! I look forward to learning from your responses.       Have:  ID Visit AE_free_text 1 1 1,4 2 1 1 3 1 2,4 4 1 1 5 1 1 6 1 3,9 7 1 3 8 1 2   Want:  ID Visit AE_num 1 1 1 1 1 4 2 1 1 3 1 2 3 1 4 4 1 1 5 1 1 6 1 3 6 1 9 7 1 3 8 1 2     Sample data: data have; input id Visit AE_free_text; cards; 1 1 1,4 2 1 1 3 1 2,4 4 1 1 5 1 1 6 1 3,9 7 1 3 8 1 2 ;   ... View more

Hello New SAS User community, I am working in a long data set with several hundred people where every participant (var id) was prescribed an antibiotic for 10 days with each line representing 1 day (var day). The dose (var dose) may change by day. I am trying to create a variable that captures the maximum duration of each dosing change As you can see in the table below, id #1 had 4 changes over time (600mg for 4 days, 0mg for 1 day, 300mg for 3 days, and then 600mg for 2 days) and id #2 had no changes. Using the data step, created a variable 'count_state' that enumerates the number of days at each dose over time, restarting when there is a change. Help: I would like to create a new variable (bold column below) that is the maximum of count_state for each dose before there is any change.   Thank you very much in advance!    id day dose count_state  max_count_state 1 1 600 1 4 1 2 600 2 4 1 3 600 3 4 1 4 600 4 4 1 5 0 1 1 1 6 300 1 3 1 7 300 2 3 1 8 300 3 3 1 9 600 1 2 1 10 600 2 2 2 1 600 1 10 2 2 600 2 10 2 3 600 3 10 2 4 600 4 10 2 5 600 5 10 2 6 600 6 10 2 7 600 7 10 2 8 600 8 10 2 9 600 9 10 2 10 600 10 10   ... View more

I am working with a long dataset of drug treatment where people can start/stop a drug and have a dose reduced/increased. Everyone in the cohort starts on the drug (drug "A"), which was part of the inclusion criteria, and are followed over 4 or 5 months. I am trying to characterize changes in drug “A” use by creating new variables that flag when/if the drug was discontinued (column 6 in want) and when/if restarted (column 7 in want) and when/if the dose was reduced (column 4 in want) and increased (column 5 in want).  The true data set is of course much more complicated, but I really need help determining the formative code. Thank you so much in advance for your help!    Have (note: system missing .  in the variable Drug_A_dose means that the drug was not taken, so 500-> . means discontinued and . ->500 or any other dose means restarted) id Month Drug_A_dose 1 1 500 1 2 500 1 3 . 1 4 . 2 1 500 2 2 500 2 3 500 2 4 250 2 5 250 3 1 500 3 2 250 3 3 250 3 4 500 3 5 100 4 1 500 4 2 . 4 3 . 4 4 500   Want (columns 4-7): id Month Drug_A_dose Drug_A_Reduce Drug_A_Increase Drug_A_discontinue Drug_A_restart 1 1 500 . . . . 1 2 500 . . . . 1 3 . . . 1 . 1 4 . . . . . 2 1 500 . . . . 2 2 500 . . . . 2 3 500 . . . . 2 4 250 1 . . . 2 5 250 . . . . 3 1 500 . . . . 3 2 250 1 . . . 3 3 250 . . . . 3 4 500 . 1 . . 3 5 100 1 . . . 4 1 500 . . . . 4 2 . . . 1 . 4 3 . . . . . 4 4 500 . . . 1   ... View more