If one uses the DEFINE command to add an interaction between two continuous, observed variables to the model, and finds the interaction to be significant, how does one probe the interaction (i.e., for "regions of significance")? I am familiar with probing interactions for regions of significance in OLS regression, but not in SEM.
I am thinking that I can probe an interaction in SEM similar to how I would do so in OLS regression: by trichotomizing one of the variables then graphing scores on the other variable in a plot.
However, the difficulty arises in that in the SEM model, the interaction term and its components can be correlated with covariates, as well as regressed on other exogenous variables. So, would the approach of trichotomizing one variable then creating a plot be too simplistic, when there are actually more complex relationships among the variables?
The Parental Education X Young Adulthood Education interaction term has four significant effects, according to Mplus results--specifically, on three of the mediators and on health.
How do I probe the interaction to make tentative conclusions about how effects of Young Adulthood Education on Young Adulthood Health "depend" on levels of Parental Education, for example? I am just unsure about approaches to probing measured variable X measured variable interactions in Mplus or in SEM more generally.