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English(EN) Lost in Aggregation: The Causal Interpretation of the IV Estimand

新论文质疑工具变量估计量的解释

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新发表在arXiv上的论文由Danielle Tsao撰写，探讨了在处理聚合处理变量时解释工具变量（IV）估计量的挑战。研究强调，聚合处理的因果效应可能存在歧义，具体取决于干预措施在组件级别上的实施方式。该论文引入了聚合约束组件干预分布（ACID）来形式化这种关系，并确定了标准IV估计量仍可提供有效解释的特定条件。 AI

排序理由 该集群包含一篇发表在arXiv上的研究论文，详细介绍了统计学中的新方法和分析。[lever_c_demoted from research: ic=1 ai=0.1]

在 arXiv stat.ML 阅读 →

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新论文质疑工具变量估计量的解释

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该集群包含一篇发表在arXiv上的研究论文，详细介绍了统计学中的新方法和分析。[lever_c_demoted from research: ic=1 ai=0.1]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Danielle Tsao, Krikamol Muandet, Frederick Eberhardt, Emilija Perkovi\'c ·

    聚合中的迷失：IV估计量的因果解释

    arXiv:2601.12120v2 Announce Type: replace-cross Abstract: Instrumental variable estimation has emerged as a standard approach to mitigating confounding bias in the social sciences and epidemiology, where conducting randomized experiments can be too costly or infeasible. However, …

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