lewisbails / cem
cem is a lightweight library for performing coarsened exact matching (CEM). CEM is a modern matching technique useful for causal inference on observational data.
☆23Updated 5 months ago
Related projects ⓘ
Alternatives and complementary repositories for cem
- difference-in-differences in Python☆93Updated 10 months ago
- Packages of Example Data for The Effect☆131Updated 2 weeks ago
- Synthetic difference in differences for Python☆66Updated 7 months ago
- Fit Sparse Synthetic Control Models in Python☆79Updated 7 months ago
- ☆17Updated 2 years ago
- Policy learning via doubly robust empirical welfare maximization over trees☆77Updated 5 months ago
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆46Updated 9 months ago
- Data for and description of the ACIC 2023 data competition☆32Updated last year
- Sufficient Representation for Categorical Variables https://arxiv.org/abs/1908.09874v1☆14Updated 4 years ago
- A python module for the synthetic control method☆54Updated 4 months ago
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆24Updated last year
- ☆92Updated 10 months ago
- Documentation and User Guide for DoubleML - Double Machine Learning in Python & R☆21Updated this week
- ☆42Updated 3 years ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆103Updated 3 years ago
- ☆81Updated 3 years ago
- A Python package for causal inference using Synthetic Controls☆170Updated 9 months ago
- CSDID☆23Updated last week
- Code associated with paper: Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models, Chernozhuk…☆15Updated 3 years ago
- Distributional Random Forests (Cevid et al., 2020)☆38Updated last year
- Confidence sequences and uniform boundaries☆56Updated 3 weeks ago
- Partition selection, point estimation, pointwise and uniform inference, and graphical procedures using binscatter methods.☆39Updated last month
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆57Updated 5 months ago
- DEPRECATED. See new generalized random forest package for up-to-date implementation.☆52Updated 7 years ago
- Unstructured Code with interesting analysis☆35Updated last month
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆25Updated 2 years ago
- Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.☆30Updated this week
- notebooks on methods for causal inference☆31Updated 3 months ago
- Fast High-Dimensional Fixed Effects Regression in Python following fixest-syntax☆176Updated this week
- Implements the Causal Forest algorithm formulated in Athey and Wager (2018).☆65Updated 4 years ago