When latent variables are included, Mplus provides R-squared estimates--which is great. However, I'm confused about a specific result. I have a model in which Mplus estimates the R-squared of a dependent variable as ranging between 0.004 and 0.871. However, this R-squared is a result of a single regression coefficient, and the STDYX estimate CI for that coefficient is -0.902 to 0.912. How can it be that the R-squared has a credible interval that doesn't contain zero when the coefficient's interval does? (For that matter, it's centered on zero!) My first thought is that the R-squared isn't being permitted to have a CI that goes below zero, since the R-squared can't go below zero--but, although that lets me interpret this output, that would make interpreting the R-squared CI difficult in some circumstances (e.g., multiple predictors that you might expect to combine to predict significantly/credibly even if no one predictor does).
This occurs in a two-level random model that terminates normally and for which the PSR is good after 2X the original number of fbiterations.