用于推断个体内关系的统计模型：随机截距交叉滞后面板模型及其解释
Statistical Models for the Inference of Within-person Relations: A Random Intercept Cross-Lagged Panel Model and Its Interpretation
AI总结：
本文探讨了随机截距交叉滞后面板模型在推断个体内关系中的应用，分析其数学关系与其他统计模型的联系，并指出其在捕捉个体间异质性时的假设特点。
摘要：
交叉滞后面板模型（CLPM）已被广泛用于推断纵向变量间的关系，尤其是在心理学领域。同时，控制个体间异质性并捕捉个体内变化过程被视为基于纵向数据因果推断的关键组成部分。由于Hamaker等人（2015）批评CLPM在推断个体内关系方面的局限性，随机截距交叉滞后面板模型（RI-CLPM）迅速普及，尤其在心理学中。尽管有许多统计模型可用于推断个体内关系，但它们之间的区别尚未明确界定，关于统计模型的解释和选择的讨论仍持续进行。本文将RI-CLPM定位为一种有用的推断个体内关系的方法，解释其实际问题，并组织其与其它统计模型的数学和概念关系，以及可能在应用中出现的潜在问题。特别是，本文指出，RI-CLPM中稳定特质因素在表示个体间异质性时的独特特征是假设它们与个体内变异不相关，这一点是其与动态面板模型等其他有前景的替代方法之间数学关系的重要联系。
英文摘要：
The cross-lagged panel model (CLPM) has been widely used, particularly in psychology, to infer longitudinal relations among variables. At the same time, controlling for between-person heterogeneity and capturing within-person relations as processes of within-person change are regarded as key components to causal inference based on longitudinal data. Since Hamaker, Kuiper, and Grasman (2015) criticized the CLPM for its limitations in inferring within-person relations, the random intercept cross-lagged panel model (RI-CLPM), which incorporates stable trait factors representing stable individual differences, has rapidly spread, especially in psychology. At the same time, although many statistical models are available for inferring within-person relations, the distinctions among them have not been clearly delineated, and discussions over the interpretation and selection of statistical models remain active. In this paper, I position the RI-CLPM as one useful method for inferring within-person relations, explain its practical issues, and organize its mathematical and conceptual relationships with other statistical models, as well as potential problems that may arise in their application. In particular, I point out that a distinctive feature of the stable trait factors in the RI-CLPM, in representing between-person heterogeneity, is the assumption that they are uncorrelated with within-person variability, and that this point serves as an important link to the mathematical relationship with the dynamic panel model, another promising alternative.
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