I have run an EFA in both MPlus and Stata and found considerable differences in the representation of the factor coefficients. Both programs indicated the same number (7) factor solution as the best fit for the data - MPlus through fit indices, Stata through Parallel Analysis.
Procedures for both:
ML extraction Oblimin rotation
While I obtained a theoretically interpretable solution in MPlus (replicated in independent CFA), Stata provides very different coefficients for the factors. Is there any reason for this and how should I approach the interpretation?
First make sure that the same sample size is used and that you are comparing the factor patterns, not the factor structure (so looking at loadings, not correlations between factors and items). If all that squares, send the outputs from the 2 programs to support.