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#treatment-effects

Every repository in the public record carrying this tag — from its GitHub topics or the keywords its package registries publish. Health is measured under the same versioned methodology as the rest of the record.

3 records
Tagged “treatment-effects”Ranked by health index
PyPI
93Exceptionalhealth index
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Python★ 8,260Aug 12, 2026
MITAug 12, 2026 · metrics 2.10.0
PyPI
89Excellenthealth index
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Jupyter Notebook · Python★ 4,752Aug 13, 2026
Custom licenseAug 13, 2026 · metrics 2.10.0
PyPI · crates.io
88Excellenthealth index
igerber/diff-diff
Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.
Python★ 350↓ 16.8K/moJul 17, 2026
MITJul 17, 2026 · metrics 2.10.0