nlapier2 / PySensemakrLinks
Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr
☆51Updated last month
Alternatives and similar repositories for PySensemakr
Users that are interested in PySensemakr are comparing it to the libraries listed below
Sorting:
- difference-in-differences in Python☆100Updated last year
- Documentation and User Guide for DoubleML - Double Machine Learning in Python & R☆21Updated this week
- Synthetic difference in differences for Python☆80Updated last year
- Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks☆99Updated 2 months ago
- Fit Sparse Synthetic Control Models in Python☆83Updated last year
- Packages of Example Data for The Effect☆140Updated 7 months ago
- Data for and description of the ACIC 2023 data competition☆32Updated 2 years ago
- A python module for the synthetic control method☆68Updated 2 months ago
- Unstructured Code with interesting analysis☆37Updated 8 months ago
- Bayesian Conjugate Models in Python☆31Updated 2 weeks ago
- Jupyter Notebook adaptation of the code from Huber (2023) - Causal Analysis☆11Updated 11 months ago
- Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference☆46Updated last week
- CSDID☆30Updated this week
- Official repository for the mcf package.☆20Updated this week
- Fast High-Dimensional Fixed Effects Regression in Python following fixest-syntax☆236Updated last week
- ☆116Updated last week
- Bayesian Causal Forests☆45Updated last year
- Repository for Introduction to Bayesian Estimation of Causal Effects☆63Updated 4 years ago
- Policy learning via doubly robust empirical welfare maximization over trees☆82Updated last year
- Distributional Random Forests (Cevid et al., 2020)☆43Updated last year
- Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.☆33Updated 4 months ago
- ☆71Updated last month
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated last month
- Educational resources☆104Updated 3 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆81Updated 6 months ago
- Delicatessen: the Python one-stop sandwich (variance) shop 🥪☆27Updated 2 weeks ago
- An R package to estimate the effect of interventions on univariate time series using ARIMA models☆22Updated last year
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆140Updated 10 months ago
- This is the repository for the Python library mlsynth☆30Updated 2 weeks ago
- The pygformula implements the parametric g-formula in Python. The parametric g-formula (Robins, 1986) uses longitudinal data with time-va…☆29Updated 3 months ago