I have recently begun using the Structural Equations Modeling (SEM) Method of confirmatory factor analysis for a research endeavor in educational science. My question is, suppose I have two latent variables each with many of its own manifest variables. If I observe a covariance between the two latent variables (I'm not sure if specifically what program I used to reach this point matters but if so I use the lavaan package in R), what does it mean?
I believe it means that it is a residual covariance indicating the presence of a common factor not shown by their predictors but I am unsure. If this is the case what would the level of residual covariance mean? i.e. is there a cut-off point where it could be considered statistically insignificant? Thank you!