Statistical Models for the Inference of Within-person Relations: A Random Intercept Cross-Lagged Panel Model and Its Interpretation

TL;DR

This paper discusses the random intercept cross-lagged panel model (RI-CLPM), clarifying its interpretation, practical issues, and relationship with other models for inferring within-person relations in longitudinal data.

Contribution

It positions RI-CLPM within the landscape of statistical models, explaining its assumptions, interpretation, and connections to other approaches for within-person inference.

Findings

RI-CLPM incorporates stable trait factors representing individual differences.

The stable trait factors are assumed uncorrelated with within-person variability.

The paper clarifies the relationship between RI-CLPM and dynamic panel models.

Abstract

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.