Hi. I am using the interrupted time series method for the first time and would greatly appreciate some guidance.
I am trying to run a single-group interrupted time series analysis on the data below. The data comprises panel data of teleconsults done by doctors on individual dates between 2022-2024. Each doctor has only one entry for a single date, but can have multiple entries for different dates through the study period. All the doctors in the dataset were subject to two interventions (first on June 30, 2023 and second on 6Mar2024). Since all doctors received the intervention, my understanding is this would be a single group ITSA analysis since technically there is no control group.
I have two questions:
I am trying to run a single-group interrupted time series analysis on the data below. The data comprises panel data of teleconsults done by doctors on individual dates between 2022-2024. Each doctor has only one entry for a single date, but can have multiple entries for different dates through the study period. All the doctors in the dataset were subject to two interventions (first on June 30, 2023 and second on 6Mar2024). Since all doctors received the intervention, my understanding is this would be a single group ITSA analysis since technically there is no control group.
I have two questions:
- How can I get the average treatment effect across all the doctors? The itsa code (below) requires a single treatment group (in this case a single doctor) to be specified, and I want to treatment effect across the whole group/all doctors in the dataset
- How can I specify two treatment start dates? The code below currently fails with two dates specified, one for the start of each treatment.
Code:
*code tsset consult_id appt_date itsa consult_activedoc, single treat(5) trperiod(06mar2024 30jun2023) lag(1) posttrend figure *data input float appt_date long consult_id float consult_activedoc byte(mandate platform_KAR) 22646 61 .03448276 0 0 22646 65 .03448276 0 0 22646 23 .3275862 0 0 22646 30 .12068965 0 0 22648 13 .03448276 0 0 22648 37 .20689656 0 0 22648 58 .36206895 0 0 22648 33 .03448276 0 0 22648 71 .4137931 0 0 22648 31 .12068965 0 0 22649 12 .1724138 0 0 22649 25 .05172414 0 0 22649 40 .27586207 0 0 22649 55 .03448276 0 0 22649 17 .13793103 0 0 22649 51 .06896552 0 0 22649 42 .01724138 0 0 22649 57 .29310346 0 0 22650 45 .13793103 0 0 22650 38 .18965517 0 0 22650 11 .0862069 0 0 22650 69 .13793103 0 0 22650 56 .1551724 0 0 22651 54 .3793103 0 0 22651 67 .1551724 0 0 22651 59 .3448276 0 0 22651 43 .05172414 0 0 22651 26 .05172414 0 0 22652 41 .2413793 0 0 22652 24 .06896552 0 0 22652 22 .12068965 0 0 22652 4 .20689656 0 0 22652 63 .10344828 0 0 22652 46 .03448276 0 0 22653 62 .10344828 0 0 22653 35 .1724138 0 0 22653 49 .1551724 0 0 22653 23 .2413793 0 0 22653 61 .13793103 0 0 22653 65 .03448276 0 0 22655 33 .01724138 0 0 22655 13 .10344828 0 0
