TABLE 1.

Results of model fit indices for the latent class models investigating National Eye Institute Visual Function (NEI VFQ-25) questionnaire data from 263 glaucoma patients. Results are given for models ranging from 1 to 5 classes.

	1 class	2 classes	3 classes	4 classes	5 classes
n, by group	263	215; 48	35; 72; 155	19; 21; 78; 145	14; 16; 18; 67; 148
Entropy	-	0.965	0.881	0.896	0.910
AIC	5382.889	4564.693	4409.870	4389.380	4395.768
BIC	5525.775	4854.037	4845.672	4971.641	5124.487
aBIC	5398.956	4597.229	4458.874	4454.853	4477.710
LMRT	-	896.273	235.791	101.944	71.220
LMRT, P value	-	<0.001	0.001	0.195	0.539
BLRT, P value	-	<0.001	<0.001	<0.001	0.333

Entropy measures accuracy of classification of participants in latent classes, values closer to 1.0 indicate better classification; AIC: Akaike information criterion, smaller values indicate better fit; BIC: Bayesian information criterion, smaller values indicate better fit; aBIC: BIC adjusted for sample size, smaller values indicate better fit; LMRT: Lo-Mendell-Rubin test and BLRT: Bootstrap likelihood ratio test, P < 0.05 indicates a model superiority to a model with one less latent class. Boldface indicates the retained class solution.