Estimation Methods for EFA in JASP
I have been struggling to understand the computational differences between the different estimation methods that JASP uses for EFA when comparing them to the "psych" package in R.
Essentially, I am trying to use an estimation method that is suited best for slight multivariate normality violation and some heteroscedasticity in the data. I thought "minres" is the best solution here because according to the psych package author it is better to use "Ordinary Least Squares (OLS) to find the minimum residual (minres) solution" (https://www.rdocumentation.org/packages/psych/versions/1.8.12/topics/fa).
However, in JASP, I can choose MINRES or Ordinary least squares separately, so I was wondering what the difference is?
Beyond that, wouldn't generalized least squares be potentially superior to minres for non-normal data (or at least weighted least squares)?
Any advice is appreciated!