Table 2. Comparison of LCA models with different latent classes based on model selection statistics .
| Number of latent class | Number of parameters estimated | G 2 | df | AIC | BIC | Maximum log-likelihood |
| 1 | 7 | 449.10 | 120 | 463.10 | 491.30 | -1771.50 |
| 2 | 15 | 251.85 | 112 | 281.85 | 342.28 | -1672.87 |
| 3 | 23 | 142.89 | 104 | 188.89 | 281.54 | -1618.39 |
| 4 | 31 | 110.98 | 96 | 172.98 | 297.85 | -1602.44 |
| 5 | 39 | 80.84 | 88 | 158.84 | 315.94 | -1587.37 |
| 6 | 47 | 65.16 | 80 | 159.16 | 348.49 | -1579.53 |
| 7 | 55 | 55.81 | 72 | 165.81 | 387.36 | -1574.85 |
| 8 | 63 | 47.58 | 64 | 173.58 | 427.36 | -1570.74 |
| 9 | 71 | 40.70 | 56 | 182.70 | 468.71 | -1567.30 |
| 10 | 79 | 32.39 | 48 | 190.39 | 508.62 | -1563.14 |
Note. LCA = latent class analysis; AIC = Akaike information criterion; BIC = Bayesian information criterion.