Table 3.
Model-Fitting Results for Univariate Latent Growth Models
| Δχ2
|
Δdf
|
p-value
|
|
|---|---|---|---|
| Tobacco Use Frequency | |||
| Linear | -- | ||
| Partly nonlineara | 559.13 | 1 | <.0001 |
| Freeb,c | -- | -- | -- |
| Alcohol Use Frequency | |||
| Linear | -- | ||
| Partly nonlineara | 180.53 | 1 | <.0001 |
| Freeb | 9.88 | 1 | .002 |
| Alcohol Use Quantity | |||
| Linear | -- | ||
| Partly nonlineara | 5.16 | 1 | .023 |
| Freeb | 83.34 | 1 | <.0001 |
| Cannabis Use Frequency | |||
| Linear | -- | ||
| Partly nonlineara | 7.45 | 1 | .006 |
| Freeb | 4.68 | 1 | .030 |
Notes. The partly nonlinear models for alcohol and cannabis use frequency freed the slope loadings for the last time point.
Comparison for chi-square test is between linear and partly nonlinear models.
Comparison for chi-square test is between partly nonlinear and free models.
Because the univariate model for tobacco use frequency contained only three times of measurement, the partly nonlinear and free models were not nested and could not be formally compared. No nested model comparisons were conducted for tobacco use quantity, as the partly nonlinear and FCSI models were just identified and therefore chi-square estimates of model fit were not available. Model comparisons for categorical outcomes were conducted using the DIFFTEST option. Model comparisons for continuous outcomes were conducted using the Satorra-Bentler scaled chi-square difference test.