使用中介比例危险回归模型进行因果推断
Hui Zeng1,2, Vernon M Chinchilli2, Nasrollah Ghahramani2
1Department of Mathematics, College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing, 100029, China.
Communications in statistics: Simulation and computation
|January 4, 2024
概括
这项研究扩展了生存数据的因果调解分析,消除了罕见的结果假设. 新的方法允许在非罕见的结果场景中使用比例危险模型计算自然直接和间接影响.
科学领域:
- 生物统计学 生物统计学
- 流行病学 流行病学
- 因果推理因果推理
背景情况:
- 与生存数据的因果调解分析对于理解复杂的健康关系至关重要.
- 范德威尔 (VanderWeele, 2011) 的现有方法依赖于比例危险模型的罕见结果假设.
- 这种限制阻碍了分析,当结果是共同的.
研究的目的:
- 扩展VanderWeele对生存数据的因果调解分析,超出罕见的结果假设.
- 在比例危险模型中开发和验证用于估计自然直接和间接影响的新方法.
- 提供适用于非罕见的时间到事件结果的实用方法.
主要方法:
- 开发了两种新的方法来估计自然的直接和间接影响,而没有罕见的结果假设.
- 通过布雷斯洛方法 (Cox模型) 或零碎常数危险模型,利用数值集成与累积基线危险估计.
- 使用模拟研究进行方法比较,并应用于ASSESS-AKI联盟数据.
主要成果:
- 成功地将因果调解分析扩展到生存数据中的非罕见结果.
- 拟议的方法提供了在特定时间点准确估计自然直接和间接影响.
- 使用模拟和现实世界的数据证明了方法的实用性.
结论:
- 开发的方法克服了先前在生存分析中因果调解的方法的局限性.
- 这些技术为研究人员提供了强大的工具,用于研究具有共同结果的时间到事件数据.
- 促进对各种与健康有关的研究中直接和间接影响的更深入的理解.
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