对重复测量的介质和结果的连续时间调解分析
Le Bourdonnec Kateline1, Valeri Linda2,3, Proust-Lima Cécile1
1Univ. Bordeaux, Inserm, Bordeaux Population Health, U1219, F-33000 Bordeaux, France.
Biometrics
|May 23, 2025
概括
这项研究引入了一种新的方法来分析纵向研究中的因果机制,特别是在痴呆症研究中的连续时间过程中. 该方法通过调解器估计影响,并考虑时间依赖的混因素.
科学领域:
- 因果推理的原因推理.
- 纵向数据分析的数据分析.
- 生物统计学 生物统计学
背景情况:
- 传统的调解分析仅限于固定的时间数据.
- 纵向研究通常涉及不规则测量的连续时间过程.
- 痴呆症研究需要时间变化的调解者和结果的方法.
研究的目的:
- 开发一种方法来估计连续时间纵向数据中的因果机制.
- 在调解分析中解决时间依赖的混问题.
- 在复杂的纵向设置中估计自然和路径特异性的影响.
主要方法:
- 为固定时间暴露,调解器和结果过程提出一种新的方法.
- 采用基于微分方程的多变量混合效应模型.
- 使用可识别性假设进行因果估计.
主要成果:
- 通过模拟评估的方法性能.
- 用来自3C大脑衰老研究的现实实例进行插图.
- 应用于教育水平,抑郁症状学,认知功能,遗传因素,血管大脑病变和神经退行.
结论:
- 拟议的方法允许在连续时间纵向数据中估计因果机制.
- 它有效地处理了时间依赖的混.
- 适用于复杂的健康研究,包括痴呆症和衰老研究.
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