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. Author manuscript; available in PMC: 2017 May 1.

Published in final edited form as: J Pain Symptom Manage. 2015 Dec 30;51(5):868–874. doi: 10.1016/j.jpainsymman.2015.12.310

Table 1.

Model Fit Indices for Latent Class Models

	Number of Classes
	1	2	3	4	5
Pearson χ²	1678.441	1241.109	954.449	649.605	613.916
LR χ²	1112.544	836.825	561.228	474.321	424.913
df	499	490	480	471	462
No. of parameters	9	19	29	39	49
Log likelihood	−5793.281	−5649.319	−5511.630	−5462.465	−5432.891
AIC	11604.561	11336.637	11081.327	11002.930	10963.782
BIC	11651.906	11436.587	11233.882	11208.090	11221.548
LMR Testing hypothesis	------	1 class vs. 2 classes	2 classes vs. 3 classes	3 classes vs. 4 classes	4 classes vs. 5 classes
LMR probability	------	< .001	< .001	< .001	.013
Entropy	------	.669	.757	.758	.692

Note: LR: Log likelihood ratio; AIC: Akaike information criterion; BIC: Bayesian information criterion; LMR: Lo-Mendell Rubin test