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AI 根据所提供的论文材料归类:摘要明确研究观测网络中的同伴因果效应、潜在同质性调整及干预的网络传播。

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关注这篇论文的作者
Shanjukta Nath
Keith Warren
Subhadeep Paul

调整潜在同质性以识别治疗社区中的同伴影响

研究问题
居民在自己退出治疗社区前观察到同伴毕业,是否影响自身毕业?研究关注如何区分同伴影响与未观测同质性造成的关联。
方法与思路
作者利用三个社区的肯定互动及进出日期构建网络,以潜变量模型调整同质性,并提出潜在位置估计误差的偏差校正及 probit 扩展。
材料陈述的贡献
摘要称估计量具有渐近无偏性,模拟中校正表现良好;应用发现同伴毕业的正向影响及群体差异,并用反事实分析考察网络传播。
阅读关注点
应核对同伴暴露的时间定义、潜在位置如何控制混杂、渐近无偏所需条件,以及干预反事实和网络传播的计算依据。
阅读边界
所给版本为 arXiv 预印本,不能据此确认同行评审或期刊接收;摘要未说明完整识别条件、效应数值及反事实分析的额外假设。

原文摘要

We investigate peer role model influence on successful graduation from Therapeutic Communities (TCs) for substance abuse and criminal behavior. We use data from 3 TCs that kept records of exchanges of affirmations among residents and their precise entry and exit dates, allowing us to form peer networks and define a causal effect of interest. The role model effect measures the difference in the expected outcome of a resident (ego) who can observe one of their peers graduate before the ego's exit vs not graduating. To identify peer influence in the presence of unobserved homophily in observational data, we model the network with a latent variable model. We show that our peer influence estimator is asymptotically unbiased when the unobserved latent positions are estimated from the observed network. We additionally propose a measurement error bias correction method to further reduce bias due to estimating latent positions. Our simulations show the proposed latent homophily adjustment and bias correction perform well in finite samples. We also extend the methodology to the case of binary response with a probit model. Our results indicate a positive effect of peers' graduation on residents' graduation and that it differs based on gender, race, and the definition of the role model effect. A counterfactual exercise quantifies the potential benefits of an intervention directly on the treated resident and indirectly on their peers through network propagation.

笔记与分组