Table 7.
Nonconvergence Rate in Study 2.
| Estimation approach | ||||||
|---|---|---|---|---|---|---|
| Variance | Sample size | Entropy | ML_E | ML_U | BCH | LTB |
| Equal | 100 | .5 | 0.4 | 8.4 | 0.0 | 0.0 |
| .6 | 0.6 | 6.0 | 0.0 | 0.0 | ||
| .7 | 0.0 | 7.2 | 0.0 | 0.0 | ||
| .8 | 0.0 | 4.6 | 0.0 | 0.0 | ||
| 200 | .5 | 1.4 | 30.8 | 0.0 | 0.0 | |
| .6 | 0.0 | 27.6 | 0.0 | 0.0 | ||
| .7 | 0.0 | 22.2 | 0.0 | 0.0 | ||
| .8 | 0.0 | 14.4 | 0.0 | 0.0 | ||
| 500 | .5 | 1.0 | 65.2 | 0.0 | 0.0 | |
| .6 | 0.2 | 53.8 | 0.0 | 0.0 | ||
| .7 | 0.0 | 32.4 | 0.0 | 0.0 | ||
| .8 | 0.0 | 10.6 | 0.0 | 0.0 | ||
| 1,000 | .5 | 0.0 | 83.4 | 0.0 | 0.0 | |
| .6 | 0.0 | 74.2 | 0.0 | 0.0 | ||
| .7 | 0.0 | 38.2 | 0.0 | 0.0 | ||
| .8 | 0.0 | 9.8 | 0.0 | 0.0 | ||
| Unequal | 100 | .5 | 3.2 | 4.8 | 0.0 | 0.0 |
| .6 | 3.0 | 3.4 | 0.0 | 0.0 | ||
| .7 | 2.4 | 1.4 | 0.0 | 0.0 | ||
| .8 | 1.8 | 1.0 | 0.0 | 0.0 | ||
| 200 | .5 | 6.4 | 19.2 | 0.0 | 0.0 | |
| .6 | 2.8 | 7.6 | 0.0 | 0.0 | ||
| .7 | 1.2 | 2.6 | 0.0 | 0.0 | ||
| .8 | 1.4 | 0.6 | 0.0 | 0.0 | ||
| 500 | .5 | 6.8 | 24.2 | 0.0 | 0.0 | |
| .6 | 0.6 | 16.4 | 0.0 | 0.0 | ||
| .7 | 0.2 | 3.6 | 0.0 | 0.0 | ||
| .8 | 0.2 | 0.4 | 0.0 | 0.0 | ||
| 1,000 | .5 | 3.6 | 7.6 | 0.0 | 0.0 | |
| .6 | 0.0 | 1.4 | 0.0 | 0.0 | ||
| .7 | 0.0 | 0.0 | 0.0 | 0.0 | ||
| .8 | 0.0 | 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.