I've been searching for a way to approach my problem.
This is a scenario from a Multivariate Statistics Assignment on Confirmatory Factor Analysis.
We've been given only a correlation matrix on 6 variables, the Standard Deviations and sample size. The model assumes that $X1$, $X2$ and $X$3 are indicators of given Factor $F1$, while $X4$, $X5$ and $X6$ are indicators of another Factor $F2$ (we actually know which factors and variables those are, but since my question is theoretical, I am keeping this simpler).
I've already evaluated the measurement model, found it has 7 degrees of freedom and moved on to the method's assumptions.
Now, assuming I want to do the Factor Extraction step using the ML estimator, which assumes data normality: is there any way I can test for my sample normality with the provided information?
I appreciate any small insights and/or directions that may help!