Table 3.
Model Fit Statistics for Latent Profile (LPA) and Confirmatory (single) Factor Analysis (CFA)
| Number of Profiles | LL | AIC | ΔAIC (vs Previous Unless Specified) | BIC | ΔBIC (vs Previous Unless Specified) | VLMR LR Test P-value (vs Previous) | LMR Adjusted LR Test P-value (vs Previous) |
|---|---|---|---|---|---|---|---|
| 1 | −949.1 | 1910.3 | – | 1930.7 | – | – | – |
| 2 | −907.8 | 1835.6 | −74.7 | 1869.6 | −61.1 | <.01 | <.01 |
| 3 | −900.4 | 1828.8 | −6.8 | 1876.5 | 6.9 | .03 | .04 |
| 4 | −892.4 | 1820.9 | −7.9 | 1882.2 | 5.7 | .10 | .11 |
| One-factor CFA | −914.5 | 1847.1 | 18.3 (vs 3-profile LPA) | 1877.8 | 1.3 (vs 3- profile LPA) | – | – |
Note: AIC, Akaike Information Criterion; BIC, Bayesian Information Criterion; LL, log-likelihood. Optimal LPA result (3 profiles) is italicized. Smaller minus LL, AIC, and BIC values suggest better fit. A significant result using the Vuong-Lo-Mendell-Rubin likelihood ratio (VLMR LR) test (threshold P < .05) to compare nested models also suggests better fit.