1) I want my primary outcome variable to be a latent factor. I am unsure where this code would go in my model, since it is neither "within" or "between" as this latent factor will be regressed on both level 2 and level 1 variables.
2) I want to add a mediator into my multilevel model. When I add in a mediation, I have to take out the random intercept. My model then runs, but I do not obtain any output. How would I be able to run a multilevel mediation and obtain output?
3) I would like to use standardized estimates, but I can only obtain stdyx once I remove the random intercept. Is there a way to get standardized output while also accounting for random intercepts?
4) Why does the multilevel model automatically run "WITH" statements even if not prompted? What would be the difference between a "WITH" between two variables at level 1 and a "WITH" between the same two variables at level 2?
5) I want to add in a variable as an aggregate at level 2 and a deviation score at level 1 (i.e. group mean centred).
The model runs properly with deviation without aggregate variables and vice versa. When I add both, the model says "the log likelihood decreased in the last EM iteration." and "The model estimation did not terminate normally due to an error in the computation." I'm not sure how to approach this, as they run well separately.
1. I am hoping to use a latent factor as my primary outcome for an SEM where I have level 1 and level 2 predictors of the level 1 latent factor (substance use). I do not think those examples apply, as I am not trying to create the latent factor at two levels, but rather use upper level variables to predict the lower level latent factor.
4. How would I go about overriding these? If I do not override them, how do I interpret the WITH statements at each level? Currently, I have my substance use variables input as manifest variables and those are the ones that are being "WITH"'d by default. These manifest substance use variables (measured at level 1) are being regressed on upper and lower level variables