Table 3.
Model | χ2 | df | CFI | SRMR | RMSEA |
---|---|---|---|---|---|
1. Configural invariance | 175.19* | 100 | .958 | .046 | .043 |
2. Metric Invariance A | 226.22* | 112 | .936 | .083 | .050 |
3. Metric Invariance B | 197.03* | 111 | .952 | .066 | .044 |
4. Scalar Invariance † | 212.66* | 119 | .947 | .067 | .044 |
Model Comparison | Δχ2 | Δdf | ΔCFI | ΔSRMR | ΔRMSEA |
1 vs. 2 | +51.03 | 12 | −.022 | +.037 | +.007 |
1 vs. 3 | +21.84 | 11 | −.006 | +.020 | +.001 |
3 vs. 4 | +15.63 | 8 | −.005 | +.001 | .000 |
Note. χ2=Chi-square. df=Degrees of Freedom. CFI=Comparative Fit Index. SRMR=Standardized Root Mean Square Residuals. RMSEA=Root Mean Square Error Approximation. Δχ2 reflects the difference in χ2 values between nested models.
p≤ .05. Metric Invariance model A: correlated error between Sad and Crying items only. Metric Invariance model B: correlated error between Sad with Crying items and Crying item released from constraints between gender.
Scalar invariance model includes a correlated error between Sad and Crying items as well as Crying item released from constraints between gender.