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Long-term Causal Inference Under Persistent Confounding via Data Combination

The dataset used in the paper is a combination of experimental and observational data for long-term causal inference. It includes short-term outcomes and long-term outcomes, and is used to estimate the average long-term treatment effect.

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Cite this as

Guido Imbens, Nathan Kallus, Xiaojie Mao, Yuhao Wang (2024). Dataset: Long-term Causal Inference Under Persistent Confounding via Data Combination. https://doi.org/10.57702/0vejcn8u

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2202.07234
Author	Guido Imbens
More Authors	Nathan Kallus Xiaojie Mao Yuhao Wang
Homepage	https://arxiv.org/abs/2203.12345