Effect of outliers on the GFI quality adjustment index in structural equation model and proposal of alternative indices

This work is intended to suggest modifications in the construction of the GFI index using robust methods for estimating the unrestricted sample covariance matrix, leading to new indices called GFI((MCD)) and GFI((MVE)). The validation of this proposal was made using Monte Carlo simulation methods, considering differences between the unrestricted sample covariance matrix and those imposed by the structural model, and different numbers of outliers generated by distributions with deviations from symmetry and excess kurtosis. It was concluded that for larger samples size (n >= 100), given that the outliers are from distributions that are symmetrical, the GFI((MCD)) and GFI((MVE)) present similar results, including samples with high percentages of outliers.