Is it the case that many of the available fit indices generated by package "psych" in R are
not appropriate for EFA, only for CFA (even though generated by package 'psych' in R for EFA)
not useful with non-normal data, because most are derived from chi-square?
I am doing EFA on skewed scale data (scale is 1-100, using PAF and oblique rotation). From the tentative runs with small and large numbers of factors I have done so far it looks as though while KMO and Bartlett and perhaps RMSEA and RMSR are going to be ok, but chi-square is significant and TLI is poor. But it seems that only R produces these indices for EFA at all - perhaps I should not be guided by them?
If I should be paying attention to them even though I am doing EFA and not CFA, are there alternatives for non-normal data? I have come across the Santorra-Bentler scaled chi-square, but this doesn’t seem to be available in package psych and it seems to be used for CFA, not EFA. Another possibility would be to bootstrap, but I am not sure how I would know whether this has been effective and that I should therefore subsequently trust the fit indices, or not.