I have ordinal, that is to say Likert-type of data, with four response categories.

Bandalos (2018) and Finney & DiStefano (2013) urge researchers to avoid traditional CFA approaches with such data.

Thus, I have run exploratory factor analysis based on a polychoric matrix as well as those based on the traditional Pearson’s R (ie, with dat treated continuously) to see if results for a CFA would differ.

I have two questions: 1. Does anyone have any good citations on comparisons of these two approaches or simulation-based studies comparing the two approaches with ordinal data?

2. gllamm can accommodate CFAs with ordinal data, correct?

Thanks