Table 3.

Fit indices for latent class analysis (N = 1224)

Model	LL	BIC	AIC	AIC3	Npar	Df	P value BLRT	Entropy R2
1-Cluster	− 16,673,248	33,559,793	33,406,497	33,436,497	30	1194	0.000	–
2-Cluster	− 14,296,688	29,027,078	28,715,375	28,776,375	61	1163	0.000	0.920
3-Cluster	− 13,280,713	27,215,535	26,745,426	26,837,426	92	1132	0.000	0.888
4-Cluster	− 12,767,201	26,408,918	25,780,403	25,903,403	123	1101	0.000	0.900
5-Cluster	− 12,457,432	26,009,785	25,222,863	25,376,863	154	1070	0.000	0.885
6-Cluster	− 12,275,281	25,865,890	24,920,562	25,105,562	185	1039	0.006	0.870
7-Cluster	− 12,132,601	25,800,935	24,697,202	24,913,202	216	1008	0.012	0.870
8-Cluster	− 12,013,512	25,783,163	24,521,023	24,768,023	247	977	0.010	0.876
9-Cluster	− 11,923,138	25,822,823	24,402,277	24,680,277	278	946	0.024	0.877
10-Cluster	− 11,830,282	25,857,516	24,278,563	24,587,563	309	915	0.016	0.877

LL log likelihood, BIC Bayesian information criterion, AIC Aikake information criterion, AIC3 Aikake information criterion 3, Npar numbers of para-meters, BLRT bootstrap likelihood ratio test