Table 5.
Comparison of factor analysis models applied to the VGAQ.
| Model | χ2 (df) | P-value | RMSEA (90% CI) | BIC | CFI | SRMR | ΔBIC | ΔCFI |
|---|---|---|---|---|---|---|---|---|
| Sex* | 0.000 | |||||||
| Configural | 741.21 (18) | 0.000 | 0.103 (0.097, 0.110) | 135492 | 0.955 | 0.034 | ||
| Metric | 824.96 (23) | 0.000 | 0.096 (0.091, 0.102) | 135531 | 0.950 | 0.045 | 39 | 0.005 |
| Scalar | 998.07 (28) | 0.000 | 0.096 (0.091, 0.101) | 135659 | 0.939 | 0.053 | 128 | 0.011 |
| Race** | ||||||||
| Configural | 420.07 (54) | 0.000 | 0.104 (0.095, 0.114) | 68714 | 0.961 | 0.032 | ||
| Metric | 450.48 (79) | 0.000 | 0.087 (0.079, 0.095) | 68539 | 0.961 | 0.038 | 175 | 0.000 |
| Scalar | 500.16 (104) | 0.000 | 0.078 (0.072, 0.085) | 68383 | 0.958 | 0.041 | 156 | 0.003 |
| Income*** | ||||||||
| Configural | 738.43 (27) | 0.000 | 0.107 (0.100, 0.113) | 125547 | 0.957 | 0.033 | ||
| Metric | 758.42 (37) | 0.000 | 0.092 (0.086, 0.98) | 125479 | 0.956 | 0.037 | 68 | 0.001 |
| Scalar | 807.85 (47( | 0.000 | 0.084 (0.079, 0.089) | 125440 | 0.954 | 0.038 | 39 | 0.002 |
*Sex (female, male)
**Race (white, black, AIAN, Asian, mixed, other)
***Income (<$50,000, $50,000-$100,000, >$100,000