Plot predicted trajectories after doing bivariate latent change score models

[maoyimin]

The bivariate latent change score models are useful to explore the dynamic relationship between two variables. However, it can be difficult to interpret the results when both level-to-change and change-to-change relationships are included and their effects are in different directions, just like the following picture:

In this situation, I find that a plot of predicted trajectories, just like what Brake et al (2018) does, is helpful to interpret this complex dynamic relationships. I hope that this function can be included in the LCSM package.

Brake, Hendrik J. van de, Frank Walter, Floor A. Rink, Peter J. M. D. Essens, and Gerben S. van der Vegt. 2018. ‘The Dynamic Relationship between Multiple Team Membership and Individual Job Performance in Knowledge-Intensive Work’. Journal of Organizational Behavior 39 (9): 1219–31. https://doi.org/10.1002/job.2260.

Thank you!

[milanwiedemann]

Thanks, I have no immediate plans to add this but agree it would be a useful feature. For now I'm posting this link here with instructions for plotting predicted scores https://thechangelab.stanford.edu/tutorials/growth-modeling/latent-change-score-modeling-lavaan/. This is mainly for myself in future if I want to add this, but others might find this a useful as well.