Rehabilitating the Lagged Dependent Variable With Structural Equation Modeling

被引：6
|
作者：
Andersen, Henrik Kenneth [1 ,2 ]
Mayerl, Jochen [1 ]
机构：
[1] Tech Univ Chemnitz, Chemnitz, Germany
[2] Tech Univ Chemnitz, Thuringer Weg 9, D-09126 Chemnitz, Germany
来源：
STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL | 2023年 / 30卷 / 04期
关键词：
Collider bias; fixed effects; lagged dependent variable; panel analysis; structural equation modeling; LATENT TRAJECTORY MODEL; BASE-LINE; MAXIMUM-LIKELIHOOD; CRITIQUE;
D O I：
10.1080/10705511.2022.2131555
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
It has been argued that including the lagged dependent variable in panel models will open up unintended back-door paths and bias the estimates of the causal variable. We show that panel analysis in the structural equation modeling framework can get around this issue. Including the lagged dependent variable has the benefit of closing back-door paths due to some unobserved time-varying con-founders. We demonstrate this by looking at simulated data and provide examples in the lavaan package for R as well as Mplus.
引用
收藏
页码：659 / 671
页数：13
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