Table 5.
Fit Indices of Measurement Invariance Testing by Gender for Four-Correlated and Four-Bifactor Models
| Model | df | χ 2 | TLI | CFI | RMSEA |
|---|---|---|---|---|---|
| 4 correlated model | |||||
| Men | 344 | 2821.29 | .87 | .88 | .09 |
| Women | 344 | 2153.15 | .90 | .91 | .07 |
| Configural invariance by gender | 688 | 5005.17 | .88 | .89 | .08 |
| Scalar invariance by gender | 791 | 5259.64 | .90 | .89 | .07 |
| Configural versus scalar model | 103 | 709.08 | |||
| 4 bifactor model | |||||
| Men | 322 | 1661.83 | .93 | .94 | .07 |
| Women1 | 297 | 1133.22 | .95 | .96 | .05 |
| Configural invariance by gender1 | 594 | 2742.33 | .94 | .95 | .06 |
| Scalar invariance by gender1 | 718 | 2729.72 | .95 | .95 | .05 |
| Configural versus scalar model | 124 | 355.04 |
Note. All analyses performed using WLSMV in MPlus. All χ2 statistics were significant at p < .001. df= degrees of freedom. TLI= Tucker-Lewis index. CFI= comparative fit index. RMSEA= root mean square error of approximation. The steps of measurement invariance are presented using gender: fit indices within each gender (Step 1 of measurement invariance testing), followed by the fit statistics when using configural (Step 2), and scalar (Step 3) solutions in the entire sample of men and women, and finally χ2 differences tests to determine if the scalar model fits significantly better than the configural model (Step 4).
SRP 8 was removed from the model to resolve model errors.