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Limits of Approximating the Median Treatment Effect

Raghavendra Addanki · Siddharth Bhandari首次提交 2024-03-15 · 修订 2024-03-15 · v1arXiv预印本

中位数处理效应的近似极限AI 解读

Average Treatment Effect (ATE) estimation is a well-studied problem in causal inference. However, it does not necessarily capture the heterogeneity in the data, and several approaches have been proposed to tackle the issue, including estimating the Quantile Treatment Effects. In the finite population setting containing $n$ individuals, with treatment and control values denoted by the potential outcome vectors $\mathbf{a}, \mathbf{b}$ , much of the prior work focused on…Average Treatment Effect (ATE) estimation is a well-studied problem in causal inference. However, it does not necessarily capture the heterogeneity in the data, and several approaches have been proposed to tackle the issue, including estimating the Quantile Treatment Effects. In the finite population setting containing $n$ individuals, with treatment and control values denoted by the potential outcome vectors $\mathbf{a}, \mathbf{b}$, much of the prior work focused on…

微观 · 因果推断微观 · 分位数与分布效应

关联记录被引 0 次 ↗OpenAlex · 核验 2026-09-30

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