Table 1. Fit Comparisons for all Models.

Outcome Measure: (Model Type)	Number of Classes†	AIC	BIC	Sample-Size Adjusted BIC	Entropy	N	Lo-Mendell-Rubin Adjusted LRT Test, p-value
Volume: (linear negative binomial model)
	1	5162.21	5201.61	5163.59	na	197	na
	2	5112.58	5148.69	5113.85	.97	13/184	-0.18, p= .0001
	3	5106.02	5151.98	5107.63	.78	90/13/94	3.301, p= .040
	4	5098.80	5154.61	5100.75	.88	160/13/12/12	0.270, p= .073
Heavy Episodic Drinking: (linear Poisson model)
	1	1450.19	1473.17	1451.00	na	197	na
	2	1439.47	1459.17	1440.16	.65	97/100	1.35, p= .001
	3	1435.48	1465.03	1436.51	.66	67/97/33	1.20, p= .002
	4	1438.63	1478.02	1440.01	.51	48/0/121/28	2.58, p= .335
Problems: (intercept Poisson model)
	1	2852.87	2869.29	2853.45	na	197	na
	2	2949.90	2959.75	2950.25	.94	26/171	0.17, p< .001
	3	2914.61	2931.02	2915.18	.82	42/26/129	1.36, p< .001
	4	2917.79	2940.78	2918.60	.83	49/26/119/3	1.38, p= .529

Note:

^†All GMMs fit with two or more classes were estimated such that one of the classes was defined as a long-term alcohol abstainer/No HED class or a long-term no-alcohol-related-problems class. Single-class solutions were estimated using zero-inflated negative binominal distributions for alcohol volume and zero-inflated Poisson distributions for HED and problems. AIC: Akaike Information Criterion, BIC: Bayesian Information Criterion, Lo-Mendell-Rubin (Lo et al., 2001) Adjusted Likelihood Ratio Test denotes change in overall model fit for a (k) versus (k+1) class model (e.g., 1- vs. 2-class model).