Table 2.

Relative Fit of One-Class Versus Two-Class Models (of 500 Samples, N = 400).

Fit statistic	Mean differencea	Mean % changea	Class membership
Skewness 0, kurtosis 0
AIC	−0.94	−0.01
BIC	−12.91	−0.16
SBIC	−3.40	−0.04
Skewness 0, kurtosis 2
AIC	25.18	0.31	Class 1 = 48 (12.08)
BIC	13.01	0.16	Class 2 = 352 (85.01)
SBIC	22.73	0.28
Skewness 0, kurtosis 4
AIC	33.66	0.41	Class 1 = 60 (14.99)
BIC	21.68	0.26	Class 2 = 340 (85.01)
SBIC	31.20	0.38
Skewness 1, kurtosis 0
AIC	37.83	0.46	Class 1 = 96 (24.00)
BIC	25.86	0.31	Class 2 = 304 (76.00)
SBIC	35.38	0.43
Skewness 1, kurtosis 2
AIC	40.94	0.50	Class 1 = 133 (33.30)
BIC	28.96	0.35	Class 2 = 267 (66.30)
SBIC	38.48	0.47
Skewness 1, kurtosis 4
AIC	49.93	0.61	Class 1 = 129 (32.21)
BIC	37.96	0.46	Class 2 = 271 (67.79)
SBIC	47.48	0.58
Skewness 1.6, kurtosis 0
AIC	104.37	1.27	Class 1 = 109 (27.36)
BIC	92.39	1.12	Class 2 = 291 (72.64)
SBIC	60.66	0.74
Skewness 1.6, kurtosis 2
AIC	72.46	0.89	Class 1 = 77 (19.15)
BIC	60.48	0.73	Class 2 = 323 (80.85)
SBIC	70.00	0.85
Skewness 1.6, kurtosis 4
AIC	71.95	0.88	Class 1 = 97 (24.26)
BIC	59.97	0.73	Class 2 = 303 (75.74)
SBIC	69.49	0.85

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.