. Author manuscript; available in PMC: 2021 Dec 1.

Published in final edited form as: J Am Acad Child Adolesc Psychiatry. 2020 Jan 20;59(12):1353–1363.e2. doi: 10.1016/j.jaac.2019.11.022

TABLE 2.

Model Fit Statistics for Latent Profile Analysis (LPA) Models With Two to Six Classes

No. of Classes	AIC^a	BIC^a	aBIC^a	LMRT p Value	PBLRT p Value	Entropy	Class Proportion Based on the Estimated Model
No. of Classes	AIC^a	BIC^a	aBIC^a	LMRT p Value	PBLRT p Value	Entropy	1	2	3	4	5	6
Two	20567	20682	20584	< .001	< .001	0.84	0.51	0.49	–	–	–	–
Three	20413	20568	20436	.02	< .001	0.82	0.40	0.32	0.28	–	–	–
Four	20318	20514	20346	.25	< .001	0.84	0.11	0.32	0.37	0.19	–	–
Five	20239	20476	20273	.12	< .001	0.85	0.10	0.28	0.20	0.29	0.12	–
Six	20183	20460	20222	.57	< .001	0.84	0.08	0.11	0.27	0.20	0.18	0.15

Note: Small p values of the LMRT and PBLRT tests indicate that the model with a greater number of classes fits the data better than the previous model. Entropy closer to 1 indicates that the children are well categorized into classes. The final model is shown in boldface type for emphasis. aBIC = sample size–adjusted Bayesian information criterion; AIC = Akaike information criterion; ASD = autism spectrum disorder; BIC = Bayesian information criterion; LMRT = Lo–Mendell–Rubin adjusted likelihood ratio test; PBLRT = parametric bootstrapped likelihood ratio test.

Lower numbers indicate more optimal model fit.