Examples#
Python: Case studies#
These are case studies with the Python package DoubleML.
General Examples#
![](../_images/examples_py_double_ml_basics_16_0.png)
Python: Basics of Double Machine Learning
![](../_images/examples_py_double_ml_pension_73_0.png)
Python: Impact of 401(k) on Financial Wealth
![](../_static/sensitivity_example_nb.png)
Python: Sensitivity Analysis
![](../_images/examples_py_double_ml_learner_13_1.png)
Python: Choice of learners
![](../_static/firststage_example_nb.png)
Python: First Stage and Causal Estimation
![](../_images/examples_py_double_ml_multiway_cluster_16_0.png)
Python: Cluster Robust Double Machine Learning
Python: Sample Selection Models
![](../_images/examples_py_double_ml_did_30_0.png)
Python: Difference-in-Differences
![](../_images/examples_py_double_ml_did_pretest_11_0.png)
Python: Difference-in-Differences Pre-Testing
![](../_static/basic_iv_example_nb.png)
Python: Basic Instrumental Variables calculation
![](../_images/examples_py_double_ml_plm_irm_hetfx_10_0.png)
Python: PLM and IRM for Multiple Treatments
Effect Heterogeneity#
![](../_images/examples_py_double_ml_gate_26_0.png)
Python: Group Average Treatment Effects (GATEs) for IRM models
![](../_images/examples_py_double_ml_gate_plr_26_0.png)
Python: Group Average Treatment Effects (GATEs) for PLR models
![](../_images/examples_py_double_ml_cate_17_0.png)
Python: Conditional Average Treatment Effects (CATEs) for IRM models
![](../_images/examples_py_double_ml_cate_plr_17_0.png)
Python: Conditional Average Treatment Effects (CATEs) for PLR models
![](../_static/sensitivity_example_nb.png)
Python: GATE Sensitivity Analysis
![](../_images/examples_py_double_ml_policy_tree_17_0.png)
Python: Policy Learning with Trees
![](../_images/examples_py_double_ml_pension_qte_38_0.png)
Python: Impact of 401(k) on Financial Wealth (Quantile Effects)
![](../_images/examples_py_double_ml_pq_44_0.png)
Python: Potential Quantiles and Quantile Treatment Effects
![](../_images/examples_py_double_ml_cvar_20_0.png)
Python: Conditional Value at Risk of potential outcomes
R: Case studies#
These are case studies with the R package DoubleML.
Sandbox#
These are examples which are work-in-progress and/or not yet fully documented.