Table 2.
Model fit indices for unconditional models with 1–7 classes (N = 1433).
| Latent Classes |
Log- likelihood |
Parameters | BIC | Difference in BIC |
aBIC | Difference in aBIC |
Entropy | BLRT |
|---|---|---|---|---|---|---|---|---|
| 1 | −22293 | 27 | 44783 | -- | 44697 | -- | 1.00 | -- |
| 2 | −12177 | 55 | 24753 | 20029 | 24579 | 20118 | 0.99 | p<.001 |
| 3 | −10670 | 83 | 21943 | 2810 | 21679 | 2900 | 0.97 | p<.001 |
| 4 | −10112 | 111 | 21029 | 914 | 20677 | 1002 | 0.96 | p<.001 |
| 5 | −9839 | 139 | 20688 | 341 | 20247 | 430 | 0.95 | p<.001 |
| 6 | −9615 | 167 | 20443 | 245 | 19912 | 335 | 0.95 | p<.001 |
| 7 | −9469 | 195 | 20353 | 90 | 19733 | 179 | 0.93 | p<.001 |
Notes:
BIC is the Bayesian information criterion, a measure of model fit; smaller values indicated better fit.
aBIC is the BIC adjusted for sample size; smaller values again indicate better fit.
Entropy is a measure of the accuracy of classification of participants in latent classes and of class differentiation; higher values indicate better classification.
BLRT is the Bootstrap likelihood ratio test, a test of the significance of differences in model fit with the addition of one more latent class; p<.05 indicates a significant change in model fit with a change in the number of latent classes.