A Critique of the Cross-Lagged Panel Model
A Critique of the Cross-Lagged Panel Model
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DOI：
10.1037/a0038889
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发表时间：
2015-03-01
影响因子：
7
通讯作者：
Grasman, Raoul P. P. P.
中科院分区：
文献类型：
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作者：
Hamaker, Ellen L.;Kuiper, Rebecca M.;Grasman, Raoul P. P. P.
许多人认为，交叉滞后面板模型（CLPM）克服了使用交叉滞后相关性作为研究纵向面板数据因果影响的方法所带来的问题。然而，本文表明，如果结构的稳定性在某种程度上具有类似于特征的定常性质，那么CLPM的自回归关系就不能充分解释这一点。因此，用CLPM获得的滞后参数不能代表实际的人际关系，这可能导致关于因果影响的存在、优势和迹象的错误结论。在本文中，我们提出了一个替代模型，通过包含随机截距将人内部过程与稳定的人之间差异分开，并讨论了该模型如何与包含交叉滞后关系的现有结构方程模型相关联。我们从CLPM和替代模型中推导出交叉滞后参数之间的分析关系，并使用模拟来证明在使用CLPM分析包含稳定的、特征样的个体差异的数据时可能出现的虚假结果。我们还提出了一种建模策略来避免这种陷阱，并使用经验数据集来说明这一点。讨论了对现有和未来交叉滞后面板研究的启示。
The cross-lagged panel model (CLPM) is believed by many to overcome the problems associated with the use of cross-lagged correlations as a way to study causal influences in longitudinal panel data. The current article, however, shows that if stability of constructs is to some extent of a trait-like, time-invariant nature, the autoregressive relationships of the CLPM fail to adequately account for this. As a result, the lagged parameters that are obtained with the CLPM do not represent the actual within-person relationships over time, and this may lead to erroneous conclusions regarding the presence, predominance, and sign of causal influences. In this article we present an alternative model that separates the within-person process from stable between-person differences through the inclusion of random intercepts, and we discuss how this model is related to existing structural equation models that include cross-lagged relationships. We derive the analytical relationship between the cross-lagged parameters from the CLPM and the alternative model, and use simulations to demonstrate the spurious results that may arise when using the CLPM to analyze data that include stable, trait-like individual differences. We also present a modeling strategy to avoid this pitfall and illustrate this using an empirical data set. The implications for both existing and future cross-lagged panel research are discussed.