Propensity Score Python Packages

morie

Multi-domain Open Research and Inferential Estimation

causalestimate

Lightweight causal inference from precomputed propensity scores and outcome predictions: IPW, AIPW, TMLE, matching, bootstrap CIs. Pandas-native.

moderndid

Scalable, GPU-accelerated Python library for modern difference-in-differences.

causallift

CausalLift: Python package for causality-based Uplift Modeling in real-world business

cbps

Python implementation of Covariate Balancing Propensity Score (CBPS) for robust causal inference in observational studies. Supports binary, multi-valued, and continuous treatments. Includes high-dimensional CBPS (hdCBPS), nonparametric CBPS (npCBPS), marginal structural models (CBMSM), and instrumental variables (CBIV).(Disclaimer: CURRENTLY WIP)