Based on my understanding of the Technical Appendices and both 1984 and 1997 Muthen papers, conditional normality is a requirement in order to calculate the conditional mean and variance of the latent variable (y*) when we have non normal covariates (x).
My question: What happens when we don't have (x) variables in our model? For example, what happens when we conduct a EFA or a CFA, in which we only have the observed variables y? Are the observed variables (y) treated as the covariates (x)? Or does the WLSMV approach correct for not having these (x) covariates?