Table 2.
Goodness-of-fit statistics for three invariance models.
| Model | χ 2 | df | CFI | ΔCFI | RMSEA | [90% CI] | |
|---|---|---|---|---|---|---|---|
| Age | Configural Invariance | 112.424 | 40 | .973 | — | .082 | [.064, .100] |
| Pattern Identity Invariance | 142.684 | 56 | .968 | −.005 | .076 | [.060, .091] | |
| Strong Factorial Invariance | 173.593 | 80 | .966 | −.002 | .066 | [.052, .079] | |
|
| |||||||
| Education | Configural Invariance | 86.280 | 24 | .977 | — | .076 | [.059, .093] |
| Pattern Identity Invariance | 99.994 | 32 | .975 | −.002 | .069 | [.054, .084] | |
| Strong Factorial Invariance | 122.958 | 44 | .971 | −.004 | .063 | [.050, .076] | |
|
| |||||||
| Ethnicity | Configural Invariance | 81.672 | 16 | .976 | — | .078 | [.061, .095] |
| Pattern Identity Invariance | 83.246 | 20 | .976 | .000 | .068 | [.053, .084] | |
| Strong Factorial Invariance | 88.732 | 26 | .977 | .001 | .060 | [.046, .073] | |
|
| |||||||
| Gender | Configural Invariance | 91.839 | 16 | .972 | — | .084 | [.067, .100] |
| Pattern Identity Invariance | 97.756 | 20 | .971 | −.001 | .076 | [.061, .091] | |
| Strong Factorial Invariance | 112.064 | 26 | .968 | −.003 | .070 | [.057, .083] | |
|
| |||||||
| Race | Configural Invariance | 67.817 | 16 | .978 | — | .073 | [.056, .091] |
| Pattern Identity Invariance | 69.539 | 20 | .979 | .001 | .064 | [.048, .080] | |
| Strong Factorial Invariance | 89.886 | 26 | .973 | −.006 | .064 | [.049, .078] | |
|
| |||||||
| Skin tone | Configural Invariance | 124.397 | 24 | .958 | — | .098 | [.081, .115] |
| Pattern Identity Invariance | 155.343 | 32 | .948 | −.010 | .094 | [.080, .109] | |
| Strong Factorial Invariance | 201.558 | 44 | .935 | −.013 | .091 | [.078, .104] | |
|
| |||||||
| Stage of Change | Configural Invariance | 79.228 | 24 | .974 | — | .071 | [.054, .089] |
| Pattern Identity Invariance | 88.925 | 32 | .973 | −.001 | .063 | [.047, .078] | |
| Strong Factorial Invariance | 145.220 | 44 | .953 | −.020 | .071 | [.059, .084] | |