Table 3.

Relative Fit of One-Class Versus Two-Class Models (of 500 Samples, N = 800).

Fit statistic	Mean differencea	Mean % changea	Class membership
Skewness 0, kurtosis 0
AIC	−1.04	−0.01
BIC	−15.09	−0.04
SBIC	−5.57	−0.03
Skewness 0, kurtosis 2
AIC	42.67	0.26	Class 1 = 63 (7.85)
BIC	28.61	0.17	Class 2 = 737 (92.15)
SBIC	38.14	0.23
Skewness 0, kurtosis 4
AIC	57.58	0.35	Class 1 = 76 (9.50)
BIC	43.53	0.27	Class 2 = 724 (90.50)
SBIC	53.05	0.32
Skewness 1, kurtosis 0
AIC	71.41	0.44	Class 1 = 149 (18.62)
BIC	57.35	0.35	Class 2 = 551 (81.38)
SBIC	66.88	0.41
Skewness 1, kurtosis 2
AIC	80.93	0.49	Class 1 = 273 (34.18)
BIC	66.87	0.41	Class 2 = 527 (65.82)
SBIC	76.40	0.47
Skewness 1, kurtosis 4
AIC	92.15	0.56	Class 1 = 232 (29.03)
BIC	78.09	0.48	Class 2 = 568 (70.97)
SBIC	87.62	0.53
Skewness 1.6, kurtosis 0
AIC	199.44	1.22	Class 1 = 264 (32.97)
BIC	185.38	1.13	Class 2 = 536 (67.04)
SBIC	194.91	1.19
Skewness 1.6, kurtosis 2
AIC	137.24	0.84	Class 1 = 154 (19.28)
BIC	123.19	0.75	Class 2 = 646 (80.72)
SBIC	132.72	0.81
Skewness 1.6, kurtosis 4
AIC	134.93	0.82	Class 1 = 216 (27.01)
BIC	120.88	0.74	Class 2 = 584 (72.99)
SBIC	130.40	0.80

Note. AIC = Akaike’s information criterion; BIC = Bayesian information criterion; SBIC = sample-corrected BIC.

^aMean difference = Fit1 − Fit2, and percentage change = (1 − Fit2/Fit1) × 100.