# Too many factors extracted from EFA!

I am constructing a scale. I have 80 items and 300 sample data. I ran EFA - Principal Axis Method of extraction and direct oblimin rotation in SPSS. I have 23 factors (using both Eigen value and parallel analysis method). After ignoring items loaded less than 0.3, I have 18 factors. I would like to reduce the constructs further down. 1. Will second order factor analysis will help? I took the total score of each factor for the same 300 sample like F1, F2 ... F18 and ran another EFA in SPSS. I now have 4 factors. Is this method appropriate and in practice? 2. Can I run CFA for these 4 factors for confirming model fit using Chi Square 1 to 3, GFI>0.9, CFI>0.9, and RMSEA<0.08 as criterias?

• 'I took the total score' - does this mean the cummulative sum across the factors (F1,F1:2,F1:3...), or simply that you used the factor scores as variable input into a second factor analysis? – ReneBt Feb 4 '19 at 8:51
• Yeah, the cummulative sum. Like x1+x2+x3..=F1. I did not calculate factor scores separately. I just tried to see how it works. Do you know how to calculate factor scores. I know there are 2-3 ways. Do you know how? – DEVIGA SUBRAMANI Feb 4 '19 at 11:28
• @ReneBt. thank you for asking this question. I understand that I have used a non-refined method. (I think it's ok). I will try using a refined method and I think Regression scores will be appropriate for my data. – DEVIGA SUBRAMANI Feb 4 '19 at 12:01