https://github.com/mepland/acic_causality_challenge_2022
Komodo Health's submission to the 2022 ACIC Causality Data Challenge
https://github.com/mepland/acic_causality_challenge_2022
Last synced: about 2 months ago
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Komodo Health's submission to the 2022 ACIC Causality Data Challenge
- Host: GitHub
- URL: https://github.com/mepland/acic_causality_challenge_2022
- Owner: mepland
- License: mpl-2.0
- Created: 2022-11-08T01:48:14.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-11T15:41:14.000Z (over 1 year ago)
- Last Synced: 2025-02-08T11:15:35.824Z (3 months ago)
- Language: Jupyter Notebook
- Size: 6.53 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
American Causal Inference Conference (ACIC)
2022 Data Challenge
Inverse Probability Weighting Difference-in-Differences (IPWDID)
Komodo Health
## Authors:
Yuqin Wei,
Matthew Epland
and Jingyuan (Hannah) Liu
## Abstract
In this American Causal Inference Conference (ACIC) 2022 challenge submission,
the canonical difference-in-differences (DID) estimator
has been used with inverse probability weighting (IPW)
and strong simplifying assumptions
to produce a benchmark model of the
sample average treatment effect on the treated (SATT).
Despite the restrictive assumptions and simple model,
satisfactory performance in both point estimate and confidence intervals was observed,
ranking in the top half of the competition.
## Paper
Published in [Observational Studies, Volume 9, Issue 3, 2023](https://muse.jhu.edu/issue/50973),
the 2022 ACIC special issue.
- [Published Paper](https://doi.org/10.1353/obs.2023.0027)
- [pdf](https://github.com/mepland/acic_causality_challenge_2022/blob/main/paper/paper_komodo_ipwdid.pdf)
## Prompt
[2022 Challenge Site](https://acic2022.mathematica.org/)
## Cloning the Repository
ssh
```bash
git clone [email protected]:mepland/acic_causality_challenge_2022.git
```
https
```bash
git clone https://github.com/mepland/acic_causality_challenge_2022.git
```
## Installing Dependencies
It is recommended to work in a [python virtual environment](https://realpython.com/python-virtual-environments-a-primer/) to avoid clashes with other installed software.
```bash
python -m venv ~/.venvs/causality
source ~/.venvs/causality/bin/activate
pip install -r requirements.txt
```