Metadata-Version: 2.4
Name: causal-toolkit-yanranhan
Version: 0.1.0
Summary: A Python package for causal inference methods including ATE estimation, propensity score methods, and meta-learners
Author: Yanran Han
License: MIT
Project-URL: Homepage, https://github.com/yanranhan95-create/causal-toolkit-yanranhan
Project-URL: Repository, https://github.com/yanranhan95-create/causal-toolkit-yanranhan
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.3.0
Requires-Dist: numpy>=1.21.0
Requires-Dist: scipy>=1.7.0
Requires-Dist: scikit-learn>=1.0.0
Requires-Dist: lightgbm>=3.3.0
Requires-Dist: patsy>=0.5.0
Dynamic: license-file

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# causal-toolkit-yanranhan

A small Python package that implements several basic causal inference estimators from the course:

Average Treatment Effect (ATE) for randomized experiments

Propensity-score methods (IPW and Doubly Robust)

Meta-learners (S-learner, T-learner, X-learner)

Double Machine Learning (binary and continuous treatment)

## Installation

```bash
uv pip install -e .
pip install git+https://github.com/yanranhan95-create/causal-toolkit-yanranhan.git
