Table 1.

Comparison of Fit of Latent Growth Curve Analysis

No. classes	LL	AIC	Adj BIC	LMR-LRT	LRT p-value	Entropy
2	−18,375.86	36,791.73	36,835.24	4,782.16	<0.0001	0.89
3	−17,636.34	35,320.34	35,372.56	1,430.74	0.0001	0.89
4	−17,009.69	34,075.39	34,225.26	1,211.75	0.0001	0.88
5	−16,557.68	33,179.36	33,248.99	874.30	0.0011	0.87
6	−16,314.60	32,701.20	32,779.52	470.18	0.0443	0.85
7	−16,095.16	32,270.32	32,357.35	424.45	0.1060	0.87

LL, log-likelihood; AIC, Aikaike Information Criterion; Adj BIC, sample size adjusted Bayesian Information Criterion; LMR-LRT, adjusted Lo–Mendell– Rubin likelihood ratio test; LRT p-value, significance (in p-value) of the adjusted LMR-LRT; Entropy (0 to 1), measures the degree to which latent classes are clearly distinguishable from 1 another. Details of the best-fitting model are indicated in bold.