sas: count number of rows according to date - sas

Question

I am working with crime data. Now, I have the following table crimes. Each row contains a specific crime (e.g. assault): the date it was committed (date) and a person-ID of the offender (person).
date person
------------------------------
02JAN2017 1
03FEB2017 1
04JAN2018 1 --> not to be counted (more than a year after 02JAN2017)
27NOV2017 2
28NOV2018 2 --> should not be counted (more than a year after 27NOV2017)
01MAY2017 3
24FEB2018 3
10OCT2017 4
I am interested in whether each person has committed (relapse=1) or not committed (relapse=0) another crime within 1 year after the first crime committed by the same person. Another condition is that the first crime has to be committed within a specific year (here 2017).
The result should therefore look like this:
date person relapse
------------------------------
02JAN2017 1 1
03FEB2017 1 1
04JAN2018 1 1
27NOV2017 2 0
28NOV2018 2 0
01MAY2017 3 1
24FEB2018 3 1
10OCT2017 4 0
Can anyone please give me a hint on how to do this in SAS?
Obviously, the real data are much larger, so I cannot do it manually.

Answer 1

One approach is to use DATA step by group processing.
The BY <var> statement sets up binary variables first.<var> and last.<var> that flag the first row in a group and the last row in a group.
You appear to be assigning the computed relapse flag over the entire group, and that kind of computation can be done with what SAS coders call a DOW loop -- a loop with the SET statement inside loop, with a follow up loop that assigns the computation to each row in the group.
The INTCK function can compute the number of years between two dates.
For example:
data want(keep=person date relapse);
* DOW loop computes assertion that relapse occurred;
relapse = 0;
do _n_ = 1 by 1 until (last.person);
set crimes; * <-------------- CRIMES;
by person date;
* check if persons first crime was in 2017;
if _n_ = 1 and year(date) = 2017 then _first = date;
* check if persons second crime was within 1 year of first;
if _n_ = 2 and _first then relapse = intck('year', _first, date, 'C') < 1;
end;
* at this point the relapse flag has been computed, and its value
* will be repeated for each row output;
* serial loop over same number of rows in the group, but
* read in through a second SET statement;
do _n_ = 1 to _n_;
set crimes; * <-------------- CRIMES;
output;
end;
run;
The process would be more complex, with more bookkeeping variables, if the actual process is to classify different time frames of a person as either relapsed or reformed based on rules more nuanced than "1st in 2017 and next within 1 year".

Answer 2

I started using sas relatively recent - I'm not by any means attempting to create perfect code here.
I'd sort the data by id/person and date first (date should be numeric), and then use retain statements check against the date of the first crime. It's not perfect, but if your data is good (no missing dates), it'll work, and it is easy to follow imho.
This only works if the first record and act of crime is supposed to happen in 2017. If you have crimes happening in 2016, and want to check whether 'a crime' is committed in 2017 and then check the relapse, then this code is not going to work - but I think that is covered in the comments beneath your question.
data test;
input tmp_year $ 1-9 person;
datalines;
02JAN2017 1
03FEB2017 1
04JAN2018 1
27NOV2017 2
28NOV2018 2
01MAY2017 3
24FEB2018 3
10OCT2017 4
;
run;
data test2;
set test;
crime_date = input(tmp_year, date9.);
act_year = year(crime_date);
run;
proc sort data=test2;
by person crime_date ;
run;
data want;
set test2;
by person crime_date;
retain date_of_crime;
if first.person and act_year = 2017 then date_of_crime = crime_date;
else if first.person then call missing(date_of_crime);
if intck('YEAR', date_of_crime, crime_date) =< 1 and not first.person
then relapse = 1;
else relapse = 0;
run;
The above code flags the act of crimes committed one year after an act of crime in 2017. You can then retrieve the unique persons with a proc sql statement, and join them with whatever dataset you have.