Table 3.

Model Selection Rates of 20 GMMs Fitted to 100 Bootstrap Samples From a Subset of the NLSY

model	key features	n classes	n param	selection rate BIC	converg rate	mean BIC	sd BIC
1	no random effects	2	12	0.000	1.00	8032.703	159.7806
2		3	19	0.000	1.00	7894.484	158.7380
3		4	26	0.000	0.98	7845.655	157.3442
4		5	33	0.001	0.92	7830.026	154.1123
5	random intercept	2	14	0	0.86	7876.661	161.6511
6		3	22	0.002	0.92	7822.524	161.3376
7		4	30	0.009	0.83	7806.706	161.3829
8	random intercept & linear slope	2	18	0.002	0.77	7824.691	151.1699
9		3	28	0.008	0.55	7773.826	147.2956
10		4	38	0.003	0.52	7822.893	149.8097
11	full random effects	2	24	0	0.77	7832.977	153.7616
12		3	37	0.002	0.47	7848.165	151.3798
13	random intercept, i on X	2	20	0.159	0.98	7785.352	154.8668
14		3	31	0.101	0.79	7812.968	157.4791
15		4	42	0.008	0.52	7823.341	148.0612
16	random intercept & linear slope, i on X	2	24	0.478	0.89	7761.509	154.7056
17		3	37	0.076	0.58	7791.234	162.0160
18		4	50	0	0.31	7792.152	143.6079
19	full random effects, i on X	2	30	0.150	0.85	7794.638	153.0162
20		3	46	0	0.34	7852.469	147.1468

Note: All models were quadratic growth mixture models. Random effects were always estimated with class-specific variance. Abbreviations: n classes = number of classes, n param = number of estimated parameters, converg rate = convergence rate, mean BIC = Bayesian Information Criterion averaged over 100 bootstrap samples, sd BIC = the standard deviation of the BIC over 100 bootstrap samples, I on X = class specific regression of the intercept factor on the covariates.