Hello all,
Updating the description of the code I am hoping to get help with:
I have a dataset where I am hoping to indicator variables that help me better organize a matched sample from my data. I have data on counties observed each week over the course of a year, some of them experienced a focal event (i.e., if P =1) and some did not and will serve as controls. Additionally, some counties experienced the focal event more than once. I want to add an indicator variable that identifies before and after these focal events at different durations for both the treatments and the non-treated counties. I need at 1 week, 2 weeks, 3 weeks, 4 weeks, and 5 weeks, but only illustrated up to 2 weeks in the example below.
In addition, would be ideal if once a county experienced a focal event they can no longer be in the control set from there forward, but it’s okay if they stay in the dataset and experience a focal event again.
I believe I need some variables such as an eventweek variable that identifies the week of the focal event, a before/after variable (0/1 if before after the focal event), a duration variable that identifies the number of weeks before and after (i.e., at 1, 2, 3, 4, and 5), and a variable (treated) that indicates that a county has been treated (after it has been treated since a county should be able to stay in the pool of controls to serve as a control until it gets treated if at all).
Essentially, I think I need to duplicate sets of observations to create windows of treated and non-treated counties around the focal events I am interested in examining. I also like to add a few other variables: (1) a variable that indicates which treatment number this is for a county (i.e., first treatment, second treatment, …) (2) a variable that indicates whether a county was treated within a short time window of a previous time it was treated (=1 if treated within <=5 time periods, 0 otherwise) and (3) a variable that indicates the degree of treatment (I want focal event variable to be binary in the wantdata but in the have data it is a actually >1 sometimes since it is a count variable), so if focal event was 2, for example, this variable would = 2. See below for example.
Also, I should note that is a focal occurred before week 6, the durations for those observations may not be able to get up to the full 5 weeks before and after. For example, if a focal event occurred in a county in week 2, I'll only have the 1 week duration for that focal event.
Thanks!
Have:
Time | ID | County | FocalEvent |
1 | 222 | ABC | 0 |
2 | 222 | ABC | 0 |
3 | 222 | ABC | 0 |
4 | 222 | ABC | 0 |
5 | 222 | ABC | 1 |
6 | 222 | ABC | 0 |
7 | 222 | ABC | 0 |
8 | 222 | ABC | 0 |
9 | 222 | ABC | 0 |
10 | 222 | ABC | 0 |
11 | 222 | ABC | 0 |
12 | 222 | ABC | 0 |
13 | 222 | ABC | 0 |
1 | 333 | BBB | 0 |
2 | 333 | BBB | 0 |
3 | 333 | BBB | 0 |
4 | 333 | BBB | 0 |
5 | 333 | BBB | 0 |
6 | 333 | BBB | 0 |
7 | 333 | BBB | 0 |
8 | 333 | BBB | 0 |
9 | 333 | BBB | 0 |
10 | 333 | BBB | 0 |
11 | 333 | BBB | 0 |
12 | 333 | BBB | 0 |
13 | 333 | BBB | 0 |
1 | 444 | CCC | 0 |
2 | 444 | CCC | 0 |
3 | 444 | CCC | 0 |
4 | 444 | CCC | 0 |
5 | 444 | CCC | 1 |
6 | 444 | CCC | 0 |
7 | 444 | CCC | 0 |
8 | 444 | CCC | 0 |
9 | 444 | CCC | 0 |
10 | 444 | CCC | 1 |
11 | 444 | CCC | 0 |
12 | 444 | CCC | 0 |
13 | 444 | CCC | 0 |
1 | 555 | DDD | 0 |
2 | 555 | DDD | 0 |
3 | 555 | DDD | 0 |
4 | 555 | DDD | 0 |
5 | 555 | DDD | 0 |
6 | 555 | DDD | 0 |
7 | 555 | DDD | 0 |
Want:
Time | ID | County | FocalEvent | EventWeek | Duration | BeforeAfter | Treated | Tnumber | Trecent | Tdegree |
4 | 222 | ABC | 0 | 5 | 1 | 0 | 1 | 1 | 0 | 0 |
5 | 222 | ABC | 1 | 5 | 1 | 1 | 1 | 1 | 0 | 0 |
4 | 333 | BBB | 0 | 5 | 1 | 0 | 0 | 0 | 0 | 0 |
5 | 333 | BBB | 0 | 5 | 1 | 1 | 0 | 0 | 0 | 0 |
4 | 444 | CCC | 0 | 5 | 1 | 0 | 1 | 1 | 0 | 0 |
5 | 444 | CCC | 1 | 5 | 1 | 1 | 1 | 1 | 0 | 0 |
4 | 555 | DDD | 0 | 5 | 1 | 0 | 0 | 0 | 0 | 0 |
5 | 555 | DDD | 0 | 5 | 1 | 1 | 0 | 0 | 0 | 0 |
9 | 444 | CCC | 0 | 10 | 1 | 0 | 1 | 2 | 0 | 0 |
10 | 444 | CCC | 1 | 10 | 1 | 1 | 1 | 2 | 0 | 0 |
9 | 333 | BBB | 0 | 10 | 1 | 0 | 0 | 0 | 0 | 0 |
10 | 333 | BBB | 0 | 10 | 1 | 1 | 0 | 0 | 0 | 0 |
3 | 222 | ABC | 0 | 5 | 2 | 0 | 1 | 1 | 0 | 0 |
4 | 222 | ABC | 0 | 5 | 2 | 0 | 1 | 1 | 0 | 0 |
5 | 222 | ABC | 1 | 5 | 2 | 1 | 1 | 1 | 0 | 0 |
6 | 222 | ABC | 0 | 5 | 2 | 1 | 1 | 1 | 0 | 0 |
3 | 333 | BBB | 0 | 5 | 2 | 0 | 0 | 0 | 0 | 0 |
4 | 333 | BBB | 0 | 5 | 2 | 0 | 0 | 0 | 0 | 0 |
5 | 333 | BBB | 0 | 5 | 2 | 1 | 0 | 0 | 0 | 0 |
6 | 333 | BBB | 0 | 5 | 2 | 1 | 0 | 0 | 0 | 0 |
3 | 444 | CCC | 0 | 5 | 2 | 0 | 1 | 1 | 0 | 0 |
4 | 444 | CCC | 0 | 5 | 2 | 0 | 1 | 1 | 0 | 0 |
5 | 444 | CCC | 1 | 5 | 2 | 1 | 1 | 1 | 0 | 0 |
6 | 444 | CCC | 0 | 5 | 2 | 1 | 1 | 1 | 0 | 0 |
3 | 555 | DDD | 0 | 5 | 2 | 0 | 0 | 0 | 0 | 0 |
4 | 555 | DDD | 0 | 5 | 2 | 0 | 0 | 0 | 0 | 0 |
5 | 555 | DDD | 0 | 5 | 2 | 1 | 0 | 0 | 0 | 0 |
6 | 555 | DDD | 0 | 5 | 2 | 1 | 0 | 0 | 0 | 0 |
8 | 444 | CCC | 0 | 10 | 1 | 0 | 1 | 2 | 0 | 0 |
9 | 444 | CCC | 0 | 10 | 1 | 0 | 1 | 2 | 0 | 0 |
10 | 444 | CCC | 1 | 10 | 1 | 1 | 1 | 2 | 0 | 0 |
11 | 444 | CCC | 1 | 10 | 1 | 1 | 1 | 2 | 0 | 0 |
8 | 333 | BBB | 0 | 10 | 1 | 0 | 0 | 0 | 0 | 0 |
9 | 333 | BBB | 0 | 10 | 1 | 0 | 0 | 0 | 0 | 0 |
10 | 333 | BBB | 0 | 10 | 1 | 1 | 0 | 0 | 0 | 0 |
11 | 333 | BBB | 0 | 10 | 1 | 1 | 0 | 0 | 0 | 0 |
