A tutorial introduction to heterogeneous treatment effect estimation with meta-learners
M Salditt, T Eckes, S Nestler - Administration and Policy in Mental Health …, 2024 - Springer
Psychotherapy has been proven to be effective on average, though patients respond very
differently to treatment. Understanding which characteristics are associated with treatment …
differently to treatment. Understanding which characteristics are associated with treatment …
DoubleML-an object-oriented implementation of double machine learning in python
P Bach, V Chernozhukov, MS Kurz… - Journal of Machine …, 2022 - jmlr.org
DoubleML is an open-source Python library implementing the double machine learning
framework of Chernozhukov et al.(2018) for a variety of causal models. It contains …
framework of Chernozhukov et al.(2018) for a variety of causal models. It contains …
How does digital tax administration affect R&D manipulation? Evidence from dual machine learning
S Pang, G Hua - Technological Forecasting and Social Change, 2024 - Elsevier
Governing firms' R&D manipulation is crucial amid the prevalent opportunism during
innovation in emerging economies. This study employs data on listed companies in China …
innovation in emerging economies. This study employs data on listed companies in China …
B-learner: Quasi-oracle bounds on heterogeneous causal effects under hidden confounding
Estimating heterogeneous treatment effects from observational data is a crucial task across
many fields, helping policy and decision-makers take better actions. There has been recent …
many fields, helping policy and decision-makers take better actions. There has been recent …
Causal Machine Learning and its use for public policy
M Lechner - Swiss Journal of Economics and Statistics, 2023 - Springer
In recent years, microeconometrics experienced the 'credibility revolution', culminating in the
2021 Nobel prices for David Card, Josh Angrist, and Guido Imbens. This 'revolution'in how to …
2021 Nobel prices for David Card, Josh Angrist, and Guido Imbens. This 'revolution'in how to …
How does “over-hype” lead to public misconceptions about autonomous vehicles? A new insight applying causal inference
Traffic accidents caused by drivers' over-reliance on SAE L2 advanced driver assistance
systems (ADAS) have become a new type of accident worthy of attention. There is growing …
systems (ADAS) have become a new type of accident worthy of attention. There is growing …
Effect or treatment heterogeneity? Policy evaluation with aggregated and disaggregated treatments
The analysis of causal effects is at the heart of empirical research in economics, political
science, the biomedical sciences, and beyond. To evaluate and design policies …
science, the biomedical sciences, and beyond. To evaluate and design policies …
Policy learning with asymmetric counterfactual utilities
Data-driven decision making plays an important role even in high stakes settings like
medicine and public policy. Learning optimal policies from observed data requires a careful …
medicine and public policy. Learning optimal policies from observed data requires a careful …
Interpretable Causal System Optimization Framework for the Advancement of Biological Effect Prediction and Redesign of Nanoparticles
Nanomedicine has promising applications in disease treatment, given the remarkable safety
concerns (eg, nanotoxicity and inflammation) of nanomaterials, and realizing the trade-off …
concerns (eg, nanotoxicity and inflammation) of nanomaterials, and realizing the trade-off …
[图书][B] Causal analysis: Impact evaluation and Causal Machine Learning with applications in R
M Huber - 2023 - books.google.com
A comprehensive and cutting-edge introduction to quantitative methods of causal analysis,
including new trends in machine learning. Reasoning about cause and effect—the …
including new trends in machine learning. Reasoning about cause and effect—the …