For decades, researchers have employed the Cross-Lagged Panel Model (CLPM) to analyze the interactions and interdependencies of a wide variety of inner- or supra-individual variables across the life course. However, in the last years the CLPM has been criticized for its underlying assumptions and several alternative models have been proposed that allow to relax these assumptions. With the Random-Intercept CLPM, the Autoregressive Latent Trajectory Model with Structured Residuals, and the Dual Change Score Model, we describe three of the most prominent alternatives to the CLPM and provide an impression about how to interpret the results obtained with these models. To this end, we illustrate the use of the presented models with an empirical example on the interplay between self-esteem and relationship satisfaction. We provide R and Mplus scripts that might help life course researchers to use these novel and powerful alternatives to the CLPM in their own research.
Beyond the Cross-Lagged Panel Model: Next-generation statistical tools for analyzing interdependencies across the life course
