在生存分析中的时间依赖媒介:因果假设的图形表示
Søren Wengel Mogensen1, Odd O Aalen2, Susanne Strohmaier3
1Department of Automatic Control, Lund University, Lund, Sweden.
Biometrical journal. Biometrische Zeitschrift
|January 30, 2026
概括
这项研究简化了复杂的因果调解分析,使用了新的"滚动图"和三角洲分离. 这种方法增强了对生存分析中的时间依赖媒介的理解,避免了复杂的反事实.
科学领域:
- 因果推理的原因推理.
- 对生存分析的分析.
- 统计建模 统计建模
背景情况:
- 传统的调解分析往往涉及复杂的反事实和跨世界的假设.
- 定向非循环图 (DAG) 变得过于复杂,有许多时间依赖的测量.
- 现有的方法在生存分析中与时间依赖的调解者作斗争.
研究的目的:
- 开发一种简化的图形方法,用于对生存数据的时间依赖调解分析.
- 引入"滚动图"和"三角形分离",作为复杂的DAG和嵌套反事实的替代方案.
- 为评估调解效应和未测量的混提供一个强大的框架.
主要方法:
- 使用治疗分离方法进行调解分析.
- 引入了"滚动图",其中节点代表整个坐标过程,简化了图形表示.
- 应用了"delta-separation"作为分析潜在循环滚动图的图形标准.
- 制定了一个调解式g公式,并将框架应用于考克斯模型.
主要成果:
- 与传统的DAG相比,滚动图为时间依赖数据提供了显著更简单的图形表示.
- 德尔塔分离有效评估调解分析条件和未测量的混杂因子的影响.
- 拟议的框架适用于治疗效应的考克斯模型等统计模型.
结论:
- "滚动图"和"三角分离"方法为时间依赖的调解分析提供了更易于处理的方法.
- 这一框架增强了对生存分析中的因果关系的评估,特别是在依赖时间的调解器中.
- 这项研究提供了一个新的图形工具,用于理解纵向数据中复杂的因果关系.
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