理解工具变量的反事实方法：实用指南

IF 2.3 3区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Asia Pacific Education Review Pub Date : 2024-07-10 DOI:10.1007/s12564-024-09982-1

Stephen Porter

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引用次数: 0

摘要

当随机化处理不可行时，工具变量是一种常用的教育因果推断方法。本文以大学一年级课程为例，回顾了成功使用工具变量估计观察数据因果效应必须满足的五个假设：SUTVA、假设随机分配、排除限制、工具对治疗的平均因果效应不为零、单调性，最后为研究人员提出建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Understanding the counterfactual approach to instrumental variables: a practical guide

Instrumental variables is a popular approach for causal inference in education when randomization of treatment is not feasible. Using a first-year college program as a running example, this article reviews the five assumptions that must be met to successfully use instrumental variables to estimate a causal effect with observational data: SUTVA, as-if random assignment, exclusion restriction, nonzero average causal effect of instrument on treatment, and monotonicity, and concludes with recommendations for researchers.

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来源期刊

Asia Pacific Education Review EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

5.20

自引率

4.30%

发文量

期刊介绍： The Asia Pacific Education Review (APER) aims to stimulate research, encourage academic exchange, and enhance the professional development of scholars and other researchers who are interested in educational and cultural issues in the Asia Pacific region. APER covers all areas of educational research, with a focus on cross-cultural, comparative and other studies with a broad Asia-Pacific context. APER is a peer reviewed journal produced by the Education Research Institute at Seoul National University. It was founded by the Institute of Asia Pacific Education Development, Seoul National University in 2000, which is owned and operated by Education Research Institute at Seoul National University since 2003. APER requires all submitted manuscripts to follow the seventh edition of the Publication Manual of the American Psychological Association (APA; http://www.apastyle.org/index.aspx).