Table 5.

Nonconvergence Rate in Study 1.

			Estimation approach
Variance	Sample size	Entropy	ML_E	ML_U	BCH	LTB
Equal	100	.5	0.0	0.0	0.0	0.0
		.6	0.0	0.0	0.0	0.0
		.7	0.0	0.0	0.0	0.0
		.8	0.0	0.0	0.0	0.0
	200	.5	0.0	0.2	0.0	0.0
		.6	0.0	0.2	0.0	0.0
		.7	0.0	0.0	0.0	0.0
		.8	0.0	0.0	0.0	0.0
	500	.5	0.0	0.0	0.0	0.0
		.6	0.0	0.0	0.0	0.0
		.7	0.0	0.0	0.0	0.0
		.8	0.0	0.0	0.0	0.0
	1,000	.5	0.0	0.0	0.0	0.0
		.6	0.0	0.0	0.0	0.0
		.7	0.0	0.0	0.0	0.0
		.8	0.0	0.0	0.0	0.0
Unequal	100	.5	2.2	11.6	0.0	0.0
		.6	4.0	8.4	0.0	0.0
		.7	6.2	2.8	0.0	0.0
		.8	6.2	0.8	0.0	0.0
	200	.5	9.8	23.6	0.0	0.0
		.6	9.8	13.4	0.0	0.0
		.7	8.2	2.8	0.0	0.0
		.8	5.4	1.2	0.0	0.0
	500	.5	19.6	24.2	0.0	0.0
		.6	12.8	8.0	0.0	0.0
		.7	7.6	1.6	0.0	0.0
		.8	3.2	0.0	0.0	0.0
	1,000	.5	15.8	18.4	0.0	0.0
		.6	9.2	1.6	0.0	0.0
		.7	3.6	0.0	0.0	0.0
		.8	0.8	0.0	0.0	0.0

Note. ML = maximum likelihood–based approach (Vermunt, 2010); BCH = BCH approach, named after the developers Bolck, Croon, and Hagennarrs (Bolck et al., 2004; Vermunt, 2010); LTB = LTB approach, named after the developers Lanza, Tan, and Bray (Lanza et al., 2013); ML_E = ML approach assuming equal variance among classes; ML_U = ML approach assuming unequal variance among classes.