This reduces the chances of the model misspecification of the moderation effect, which can happen when relying strongly on inappropriate theoretical assumptions (such as misusing a cubic polynomial curve to fit what should be a bounded S-shaped age development effect). (4 / 4)

What's special about this approach in this tutorial is that it shows the first fit of the most flexible nonparametric nonlinear model exploratively. Then confirm if a hypothesized model (e.g., quadratic) sufficiently describes the data by comparing it to the flexible model. (3 / 4)

LSEM is a flexible, nonparametric method for analyzing nonlinear moderation effects in SEM without needing to categorize variables (such as age groups) or assume a specific form of a nonlinear function. (2 / 4)