Latent change scores models for applied research: A practical guide using Mplus

The present article provides a practical guide for modelling and interpreting several basic applications of the latent change scores (LCS) model, a useful and flexible approach for the analysis of change. The article is addressed to students, researchers and practitioners who are familiar with structural equation modelling but new to LCS. We first provided a gentle introduction to the LCS model using non-technical language and minimal mathematical formalism. We illustrated the basic ideas behind this approach, introducing LCS in its simplest form. We show how this model can be straightforwardly extended to more complex applications, including the dual change score (DCS) model and some of its variants (i.e., the proportional change and the constant change models). We illustrated how the univariate LCS model can be used to determine the growth trajectory of a variable across multiple waves of assessment. Next, we focused on the bivariate case, which allows for the modelling of the dynamic relations between two variables. For each model, we provided easy-to-follow examples of applications based on Schwartz's theory of basic personal values. The examples are accompanied by annotated syntax and output showing how they can be implemented with the Mplus software and how results can be interpreted.