Table 1.
Log likelihood |
BIC | SSA-BIC | AIC | Entropy | LRT | BLRT | |
---|---|---|---|---|---|---|---|
1-class | −2067.02 | 4176.67 | 4151.32 | 4150.04 | - | - | - |
2-class | −2007.53 | 4073.68 | 4038.82 | 4037.07 | .965 | .0009 | <.00001 |
3-class | −1975.70 | 4025.98 | 3981.62 | 3979.39 | .933 | .20 | <.0001 |
4-class | −1955.90 | 4002.38 | 3948.51 | 3945.80 | .931 | .22 | <.00001 |
5-class | −1935.94 | 3978.44 | 3915.07 | 3911.88 | .928 | .18 | <.00001 |
6-class | −1918.53 | 3959.59 | 3886.72 | 3883.05 | .932 | .19 | <.0001 |
Note. BIC=Bayesian Information Criterion; SSA-BIC=Sample-size adjusted Bayesian Information Criterion; AIC=Akaike Information Criterion; LRT=Lo-Mendell-Rubin Adjusted Likelihood Ratio Test; BLRT=Parametric Bootstrapped Likelihood Ratio Test. Smaller BIC, SSA-BIC, and AIC values, and higher entropy values indicate better fitting models; significant values for the LRT and the BLRT quantify the likelihood that the data can be better described by a model with one less trajectory.