https://github.com/sodascience/schools_synth_test
Test code for disaggregated synthetic control with simulated data
https://github.com/sodascience/schools_synth_test
causal-inference simulation statistics synthetic-control
Last synced: about 1 year ago
JSON representation
Test code for disaggregated synthetic control with simulated data
- Host: GitHub
- URL: https://github.com/sodascience/schools_synth_test
- Owner: sodascience
- License: mit
- Created: 2023-07-14T06:51:32.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-01-17T09:28:56.000Z (over 2 years ago)
- Last Synced: 2025-01-25T12:09:36.638Z (over 1 year ago)
- Topics: causal-inference, simulation, statistics, synthetic-control
- Language: R
- Homepage:
- Size: 11 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Disaggregated synthetic control simulation
In this repository, we simulate data on a school intervention and we try to recover the average causal effect using a disaggregated synthetic control method. In this method, we create a synthetic control for each school and then average over schools.
The script [`01_simulate_data.R`](./01_simulate_data.R) contains the code to create the simulated school data, which results in the following simulated effect:

The script [`02_disaggregated_synthetic_control.R`](./02_disaggregated_synthetic_control.R) contains the code to analyse this data and produce school-level effect plots like this:

Additionally, there is code to investigate covariate balance for the schools:

## Contact
This is a project by the [ODISSEI Social Data Science (SoDa)](https://odissei-data.nl/nl/soda/) team.
Do you have questions, suggestions, or remarks on the technical implementation? File an issue in the
issue tracker or feel free to contact [Erik-Jan van Kesteren](https://github.com/vankesteren).