. Author manuscript; available in PMC: 2021 Feb 18.

Published in final edited form as: Dev Psychopathol. 2020 Oct;32(4):1323–1334. doi: 10.1017/S0954579420000735

Table 2.

Model fit statistics and estimated class proportions for latent profile models with two to five classes.

Number of classes	AIC^a	BIC^a	aBIC^a	Entropy	VLMRT	LMRT	BLRT	Class proportion based on the estimated model
Number of classes	AIC^a	BIC^a	aBIC^a	Entropy	VLMRT	LMRT	BLRT	1	2	3	4	5
Two	3182	3222	3181	0.95	<0.001	<0.001	<0.001	0.14	0.86	–	–	–
Three	3151	3207	3150	0.82	0.27	0.28	<0.001	0.12	0.24	0.64	–	–
Four	3131	3203	3130	0.87	0.09	0.11	<0.001	0.05	0.09	0.22	0.64	–
Five^b	3130	3217	3128	0.78	0.55	0.56	1.0	0.05	0.08	0.26	0.15	0.46

Lower numbers indicate more optimal model fit.

Reported model did not replicate after 10,000 random starts.

Note. AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; BIC = Sample Adjusted Bayesian Information Criterion; VLMRT = Vo-Lo-Mendell-Rubin Likelihood Ratio Test; LMRT = Lo-Mendell-Rubin Adjusted Likelihood Ratio Test; BLRT = parametric bootstrapped likelihood ratio test. Small p-values of the VLMRT, LMRT, and BLRT tests indicate that the model with a greater number of classes fits the data better than the previous model. Entropy closer to 1 indicates the children are well categorized into classes.