Beyond the Cross-Lagged Panel Model: Next-generation statistical tools for analyzing interdependencies across the life course
Section snippets
Cross-Lagged Panel Model
The CLPM is the standard model to examine rank-order changes and time-lagged associations between two longitudinally assessed variables (see Fig. 1 for a CLPM with four measurement waves). It provides two types of coefficients that are of particular interest to life course researchers. First, the autoregressive paths (a1 and a2 in Fig. 1) provide information on the rank-order stability of x or y, respectively (i.e., the stability of inter-individual differences; Mund, Zimmermann, & Neyer, 2018
Three alternatives to the CLPM
In the following, we describe the Random-Intercept CLPM (RI-CLPM), the Autoregressive Latent Trajectory Model with Structured Residuals (ALT-SR), and the Dual Change Score Model (DCSM). After having introduced these models, we will compare them to each other concerning some central aspects as well as to the multilevel growth model and the fixed effects regression model.
Empirical illustration
After having introduced the CLPM and three contemporary alternative approaches, we illustrate the interpretation of all models by an empirical example on the interplay between self-esteem (SE) and relationship satisfaction (RS). The reciprocal influences between these two variables have often been studied to investigate to what extent aspects of social relationships are influenced by and likewise further influence trait-like personality characteristics (e.g., Erol & Orth, 2014; Mund, Finn,
Conclusion
Trying to understand the life course of individuals is an ambitious endeavor that requires a tailored set of tools regarding study design, data collection, and data analysis (Bernardi et al., 2018). Across their life course, individuals navigate through and interact in different contexts. These interactions between two complex systems (individual and environment) as well as interactions within individuals create a set of interdependencies that need to be investigated when trying to understand
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