关于模拟双向反循环在门德尔随机化研究中的注意事项
Liang-Dar Hwang1, David M Evans2,3,4
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
Behavior genetics
|May 31, 2024
概括
具有反循环的结构方程模型 (SEM) 对单个暴露-结果关系的仪器变量 (IV) 估计器没有一致性优势. 有限样本功率根据剩余相关性和仪器强度而变化.
科学领域:
- 因果推理的原因推理.
- 计量经济学 计量经济学
- 生物统计学 生物统计学
背景情况:
- 有反循环的结构方程模型 (SEM) 建议用于分析双向关系.
- 传统的仪器变量 (IV) 估计器是因果效应估计的标准.
研究的目的:
- 为了比较SEM与反循环的一致性和有限样本功率与传统IV估计器.
- 调查剩余相关性和仪器强度对这两种方法性能的影响.
主要方法:
- 该研究从理论上分析了使用简单的双向线性反循环的SEM.
- 与传统的IV估计器进行比较 (瓦尔德估计器/2阶段最小平方).
- 在各种条件下检查有限样本属性.
主要成果:
- 带有反循环的SEM与IV估计器相比,对于单个暴露-结果关系,没有一致性优势.
- 有限样本功率是可比的,性能取决于剩余相关性和仪器强度.
- 剩余相关性不会影响SEM功率,而IV功率对其敏感.
结论:
- 对于单次曝光结果双向关系,带有反循环的SEM不会比IV估计器提高一致性.
- 在SEM和IV之间做出选择可能取决于特定的数据特征,如剩余相关性和仪器强度.
- 进一步的研究可能会探索复杂的反循环结构,在这种情况下,SEM可能会带来优势.
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