在交叉滞后模型中适当建模内原性:辅助变量和模型隐含的仪器变量的效率
Junyan Fang1,2, Zhonglin Wen3, Kit-Tai Hau4
1Public Courses Teaching Department, Guangzhou Sport University, Guangzhou, China.
Behavior research methods
|March 20, 2025
概括
内基性偏差纵向交叉滞后面板模型 (CLPM). 仪表变量 (IV) 方法,特别是模型隐含的IV (MIIV),有效地减轻了这种偏差,以获得更准确的因果推理.
科学领域:
- 社会科学 社会科学 社会科学
- 心理学 心理学 心理学
- 计量经济学 计量经济学
背景情况:
- 内源性在纵向研究中构成了重大挑战,可能会导致结果偏差.
- 交叉滞后面板模型 (CLPM) 被广泛使用,但容易受到内源性问题的影响.
- 现有的方法不足以解决CLPM的内源性,导致过高估计的因果关系.
研究的目的:
- 调查内源性对CLPM的影响.
- 评估仪表变量 (IV) 方法,特别是辅助IV (AIV) 和模型隐含IV (MIIV) 的有效性,以解决内源性问题.
- 为了比较AIV-CLPM和MIIV-CLPM在缓解偏差和改善因果推断方面的表现.
主要方法:
- 进行模拟以评估CLPM中的内源性偏差.
- 在各种条件下评估了AIV-CLPM和MIIV-CLPM的性能.
- 利用经验数据集来证明MIIV-CLPM的实际应用.
主要成果:
- 内源性显著偏差了CLPM,高估了交叉滞后效应.
- 艾维-CLPM显示了减少但仍然相当大的偏差,具有低的稳定性和高的I型错误率.
- MIIV-CLPM提供了更准确的估计,更少的I型错误,以及具有足够样本大小的中等统计能力.
结论:
- MIIV-CLPM是一种优越的方法,用于缓解跨滞后模型中的内源性偏差.
- 在纵向研究中,MIIV-CLPM方法为更可靠的因果推断提供了实用和可行的解决方案.
- 这些发现得到了模拟和经验说明的支持,突出了MIIV方法的概括性.
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