The normed chi-square is given by χ2/df, and its value should be 3 or less to indicate a better fit between the observed and modeled values (Hair et al. 2010). NFI is the ratio of the difference in the value of χ2 between the fitted and null models, divided by the value of χ2 for the null model (NFI = 1 is a perfect model; Hair et al. 2010). Bentler (1992) suggested that the value of NFI should be 0.90 or above.