Table 2.
Unconditional model parameters for the second-order latent growth models.
Model | Y-B χ2 | df | CFI | RMSEA [95% CI] | Slope |
Intercept variance | |
---|---|---|---|---|---|---|---|
Mean | Variance | ||||||
Phonological awareness | |||||||
Blending | 52.79** | 26 | .96 | .06 [.03-.08] | 1.52*** | 0.71** | 5.49*** |
Elision | 65.88*** | 25 | .96 | .07 [.05-.09] | 1.73*** | 1.22** | 9.25*** |
Rhyme | 28.23*** | 6 | .97 | .10 [.07-.14] | 0.97*** | 1.26*** | 3.56*** |
Composite | 626.87*** | 255 | .89 | .07 [.06-.07] | 1.43*** | 0.44** | 4.78*** |
Letter knowledge | |||||||
Names | 1.18ns | 2 | 1.00 | .00 [.00-.09] | 2.96*** | 10.86*** | 90.74*** |
Sounds | 7.79ns | 3 | .98 | 0.7 [.00-.13] | 0.82*** | 0.25ns | 3.12*** |
Note. In the letter-sound knowledge model, residuals were constrained to equality across all three time points so that variance of slope and intercept could be estimated.
p > .05.
p < .01.
p < .001.