Application of a Combined System Dynamics and Structural Equation Modeling Approach

Music City Center 

Methods for modeling causal relations differ in their underlying assumptions. Structural Equation Modeling (SEM) is a multivariate statistical technique for analyzing relationships among observed and latent variables, while System Dynamics (SD) considers the whole systemic structure to model multilevel feedback systems. SD models nonlinear feedback and dynamic changes, while in incorporating such characteristics, SEM requires special considerations to deal with the issue of model identifiability. SEM is a powerful tool in psychometrics, an application that can greatly enhance SD models. Previous attempts to link SD and SEM have been limited to specific questions and illustrative examples instead of a general framework. Our generative framework bridges SD and SEM. We illustrate how SD and SEM can be articulated within this framework and complement each other by evaluating the relationship between systems thinking and ecological worldview among undergraduate psychology students (N = 1058).

structural equation modeling

system dynamics modeling

latent variable

model identifiability

feedback loop

model fit