rlirey / psmatchingLinks
Propensity score matching in Python 3
☆26Updated 2 years ago
Alternatives and similar repositories for psmatching
Users that are interested in psmatching are comparing it to the libraries listed below
Sorting:
- ☆104Updated 4 years ago
- EconML/CausalML KDD 2021 Tutorial☆162Updated 2 years ago
- ☆289Updated 2 years ago
- A Python package for propensity score matching☆54Updated 3 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆65Updated last year
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆70Updated 4 months ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (Python version)☆20Updated 4 years ago
- A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.☆22Updated 8 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆62Updated 4 years ago
- propensity score matching in python☆59Updated last month
- Some notes on Causal Inference, with examples in python☆154Updated 5 years ago
- Causal Inference in Python☆573Updated 2 months ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆335Updated 10 months ago
- Code and documentation for experiments in the TreeExplainer paper☆185Updated 5 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆147Updated last year
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆90Updated 2 years ago
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆69Updated 5 years ago
- Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementati…☆143Updated 4 years ago
- Breast cancer prediction using causal Inference☆11Updated 3 years ago
- A Random Survival Forest implementation for python inspired by Ishwaran et al. - Easily understandable, adaptable and extendable.☆60Updated 9 months ago
- Code for Colangelo and Lee (2025)☆14Updated 7 months ago
- 💊 Comparing causality methods in a fair and just way.☆140Updated 5 years ago
- This repository is a tutorial about survival analysis based on advanced machine learning methods including Random Forest, Gradient Boosti…☆33Updated 6 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆63Updated 4 months ago
- Python implementation of iterative-random-forests☆67Updated last year
- ☆72Updated 4 years ago
- Bayesian Additive Regression Trees For Python☆231Updated last year
- CausalLift: Python package for causality-based Uplift Modeling in real-world business☆350Updated 2 years ago
- A Python package for causal inference using Synthetic Controls☆189Updated last year