用多个有序介质对自然间接效应进行多次可靠的估计.
An-Shun Tai1, Sheng-Hsuan Lin2
1Department of Statistics, National Cheng Kung University, Tainan, Taiwan.
Statistics in medicine
|December 11, 2023
概括
本研究在多重调解分析中引入了自然间接效应 (NIE) 的多重可靠估计器,为模型错误规范提供了更好的保护. 与现有方法相比,模拟和肝病例证明了它们的有效性.
科学领域:
- 因果推理的原因推理.
- 统计方法学的统计方法.
- 生物统计学 生物统计学
背景情况:
- 多重调解分析对于理解使用多个调解者的复杂因果途径至关重要.
- 现有的方法,如G计算和自然间接效应 (NIE) 的反向概率权重,容易导致模型错误规范.
- 目前还缺乏用于多个调解分析的强有力的方法,特别是与有序调解员的调解方法.
研究的目的:
- 提出一种新的方法,使用多重可靠的自然间接效应 (NIEs) 估计器,在多个有序调解器的存在下.
- 开发可靠的估计器来模拟错误规范,这是当前方法的一个关键局限性.
- 为复杂的因果路径分析提供统计学上健全和可靠的工具.
主要方法:
- 开发自然间接影响 (NIE) 的多倍可靠估计器.
- 在常规条件下,理论分析表明一致性和非对称的正常性.
- 模拟研究用于与现有方法比较有限样本属性.
- 应用到台湾肝病患者的现实数据集.
主要成果:
- 拟议的多重稳定估计器证明了对模型错误规范的稳定性.
- 估计器被证明是一致的和异常正常的.
- 与现有方法相比,模拟结果显示了有利的有限样本特性.
- 该方法已成功应用于分析肝病进展中介作用.
结论:
- 拟议的多重可靠估计器为多重调解分析提供了更可靠的方法,特别是当模型规格不确定时.
- 这种方法通过提供自然间接效应 (NIE) 的可靠估计来增强因果推理.
- 随着R包"MedMR"的可用性,这种先进的统计技术的实际应用变得更加容易.
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