I am writing my doctorate thesis and testing the developped hypotheses by calculating a SEM. Unfortunetly, even though I deleted lots of items and even some factors (based on a reliability analysis, an exploratory factory analysis, the measurement model with all items and a confirmatory factor Analysis). However the fit indeces are still poor. Now I really dont know what to do. Ad-hoc modifications (additional paths and co-variances) would be an option I just tried and they enhance the fit indices – however as far as I know this is not a good approach and also from the output I see that some paths and co-variances just dont make sence. Therefore, I am really lost. What would be a common approach? Do I really have to start again and developping a new model oder conducting the Survey again? I would really appreciate any help!
Solved – Bad Model Fit indices – SEM
structural-equation-modeling
Best Answer
Did you check the normality of underlying variables? Maybe they are terribly non-normal. You can transform using Box-Cox (in Excel), ranking, or the two-step transformation (see https://www.youtube.com/watch?v=twwT6FgwlAo).