Table 1 Structural model adjustment criteria

Chi-square (CMIN) and Chi-square per degrees of freedom (CMIN/df)

Tests the H₀ that the residual covariance estimate is equal to a matrix composed only by zeros. It considers the degrees of freedom (df) of χ². The chi-square value is divided by the number of degrees of freedom to obtain an adjustment value for the model less sensitive to the sample size.

Table value χ²; values below 5 are tolerable.

Comparison of values obtained χ² with the tabulated value given by df.

Root square mean error of approximation (RMSEA)

Identify how well a model fits the population, not just the sample used for the estimation.

Ideal values up to 0.08; below 0.10 are tolerable

A value between 0.05 and 0.08 indicates a good approximation

Normed Fit Index (NFI)

Compare the chi-square for the tested model against the chi-square for the baseline model assuming that the measured variables are completely independent.

0 (has no adjustment) and

1 (perfect fit)

A value close to 0.90 or 0.95 reflects a good adjustment

Comparative Fit Index (CFI)

Comparative adjustment index is considered to be more appropriate for the evaluation of models generated from samples considered small

It shows whether and to what extent the quality of adjustment of the proposed model is better than that of the base model.

A value close to 0.90 or 0.95 reflects a good adjustment