Table 1.
Class enumeration results: Proportion of 500 randomly generated datasets that selected K classes for data generated with 3 classes and 100 subjects per class by estimation method, selection criterion, and correlation structure and level assumed when generating the data.
| LCTA Method | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
|
| ||||||||||
| Generated as | AIC | BIC | Sample Size Adjusted BIC | |||||||
|
| ||||||||||
| True ∑ | True ρ | K = 2 | K = 3 | K = 4+ | K = 2 | K = 3 | K = 4+ | K = 2 | K = 3 | K = 4+ |
|
| ||||||||||
| I = AR(1) = CS | 0.00 | 0.00 | 0.84 | 0.16 | 0.00 | 1.00 | 0.00 | 0.00 | 0.85 | 0.15 |
| AR(1) | 0.05 | 0.00 | 0.71 | 0.29 | 0.00 | 0.99 | 0.01 | 0.00 | 0.74 | 0.26 |
| AR(1) | 0.10 | 0.00 | 0.39 | 0.61 | 0.00 | 0.98 | 0.02 | 0.00 | 0.46 | 0.54 |
| AR(1) | 0.25 | 0.00 | 0.01 | 0.99 | 0.00 | 0.45 | 0.55 | 0.00 | 0.00 | 1.00 |
| AR(1) | 0.50 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 |
| CS | 0.05 | 0.00 | 0.60 | 0.40 | 0.00 | 0.98 | 0.02 | 0.00 | 0.67 | 0.33 |
| CS | 0.10 | 0.00 | 0.19 | 0.81 | 0.00 | 0.83 | 0.17 | 0.00 | 0.23 | 0.77 |
| CS | 0.25 | 0.00 | 0.00 | 1.00 | 0.00 | 0.03 | 0.97 | 0.00 | 0.00 | 1.00 |
| CS | 0.50 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 |
|
| ||||||||||
| CPMM Method Modeled as AR(1) | ||||||||||
|
| ||||||||||
| Generated as | AIC | BIC | Sample Size Adjusted BIC | |||||||
|
| ||||||||||
| True ∑ | True ρ | K = 2 | K = 3 | K = 4+ | K = 2 | K = 3 | K = 4+ | K = 2 | K = 3 | K = 4+ |
|
| ||||||||||
| I = AR(1) = CS | 0.00 | 0.00 | 0.71 | 0.29 | 0.00 | 1.00 | 0.00 | 0.00 | 0.84 | 0.16 |
| AR(1) | 0.05 | 0.00 | 0.76 | 0.24 | 0.00 | 1.00 | 0.00 | 0.00 | 0.86 | 0.14 |
| AR(1) | 0.10 | 0.00 | 0.75 | 0.25 | 0.00 | 1.00 | 0.00 | 0.00 | 0.89 | 0.11 |
| AR(1) | 0.25 | 0.00 | 0.74 | 0.26 | 0.16 | 0.84 | 0.00 | 0.00 | 0.87 | 0.13 |
| AR(1) | 0.50 | 0.11 | 0.68 | 0.20 | 0.75 | 0.25 | 0.00 | 0.20 | 0.69 | 0.11 |
| CS | 0.05 | 0.00 | 0.59 | 0.41 | 0.00 | 1.00 | 0.00 | 0.00 | 0.76 | 0.24 |
| CS | 0.10 | 0.00 | 0.30 | 0.70 | 0.00 | 0.95 | 0.05 | 0.00 | 0.46 | 0.54 |
| CS | 0.25 | 0.00 | 0.01 | 0.99 | 0.00 | 0.35 | 0.65 | 0.00 | 0.02 | 0.98 |
| CS | 0.50 | 0.00 | 0.00 | 1.00 | 0.00 | 0.01 | 0.99 | 0.00 | 0.00 | 1.00 |
|
| ||||||||||
| CPMM Method Modeled as CS | ||||||||||
|
| ||||||||||
| Generated as | AIC | BIC | Sample Size Adjusted BIC | |||||||
|
| ||||||||||
| True ∑ | True ρ | K = 2 | K = 3 | K = 4+ | K = 2 | K = 3 | K = 4+ | K = 2 | K = 3 | K = 4+ |
|
| ||||||||||
| I = AR(1) = CS | 0.00 | 0.00 | 0.71 | 0.29 | 0.03 | 0.97 | 0.00 | 0.00 | 0.83 | 0.17 |
| AR(1) | 0.05 | 0.00 | 0.62 | 0.38 | 0.10 | 0.89 | 0.00 | 0.00 | 0.79 | 0.21 |
| AR(1) | 0.10 | 0.00 | 0.50 | 0.50 | 0.19 | 0.81 | 0.01 | 0.01 | 0.67 | 0.32 |
| AR(1) | 0.25 | 0.00 | 0.09 | 0.91 | 0.43 | 0.45 | 0.12 | 0.01 | 0.19 | 0.80 |
| AR(1) | 0.50 | 0.00 | 0.01 | 0.99 | 0.03 | 0.57 | 0.40 | 0.00 | 0.05 | 0.95 |
| CS | 0.05 | 0.00 | 0.79 | 0.21 | 0.15 | 0.85 | 0.00 | 0.01 | 0.88 | 0.11 |
| CS | 0.10 | 0.01 | 0.74 | 0.25 | 0.28 | 0.72 | 0.00 | 0.03 | 0.86 | 0.11 |
| CS | 0.25 | 0.05 | 0.72 | 0.23 | 0.59 | 0.41 | 0.00 | 0.09 | 0.79 | 0.12 |
| CS | 0.50 | 0.04 | 0.77 | 0.19 | 0.53 | 0.47 | 0.00 | 0.07 | 0.85 | 0.08 |
(1) I = Independent; AR(1) = auto-regressive lag 1; CS = compound symmetric; LCTA method always modeled as Independent