anishazaveri / austen_plots
Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".
☆27Updated 3 years ago
Alternatives and similar repositories for austen_plots:
Users that are interested in austen_plots are comparing it to the libraries listed below
- ☆93Updated last year
- Bayesian Causal Forests☆41Updated 8 months ago
- Policy learning via doubly robust empirical welfare maximization over trees☆78Updated 7 months ago
- Repository for Introduction to Bayesian Estimation of Causal Effects☆58Updated 4 years ago
- Code to run submissions for the Atlantic Causal Inference Competition☆42Updated 5 months ago
- Tools for causal discovery in R☆18Updated 7 months ago
- Design of Simulations using WGAN☆48Updated 2 years ago
- R and python implementations of Accelerated Bayesian Causal Forest.☆25Updated 6 months ago
- R package cfcausal☆27Updated 2 years ago
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- Data for and description of the ACIC 2023 data competition☆32Updated last year
- ☆42Updated 3 years ago
- Paper Repository☆11Updated 2 years ago
- Approximately balanced estimation of average treatment effects in high dimensions.☆34Updated 3 years ago
- Simulating Longitudinal and Network Data with Causal Inference Applications☆65Updated 5 months ago
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆13Updated 2 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆15Updated 4 years ago
- Packages of Example Data for The Effect☆135Updated 2 months ago
- ☆13Updated 7 months ago
- R package for doubly robust estimates of causal effects in high-dimensions using flexible Bayesian methods☆26Updated last month
- Course material for the PhD course in Advanced Bayesian Learning☆57Updated 2 months ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆104Updated 3 years ago
- Adjustment Identification Distance: A gadjid for Causal Structure Learning☆9Updated 6 months ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 2 years ago
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆48Updated last month
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆56Updated 7 months ago
- Code for Colangelo and Lee (2022)☆12Updated 7 months ago
- Targeted Maximum Likelihood Estimation for a binary treatment: A tutorial. Statistics in Medicine. 2017☆16Updated 4 years ago
- Tutorial_Computational_Causal_Inference_Estimators☆31Updated 3 years ago
- R/haldensify: Highly Adaptive Lasso Conditional Density Estimation☆17Updated last month