TABLE 4.
Estimates (standard errors) of the rater-specific AUC are obtained under different models: Gaussian random effect (GRE) and finite mixture (FM) models from Albert (2007), Dorfman-Berbaum-Metz (DBM) method from Dorfman et al. (1992), and our proposed model.
| Estimated rater-specific AUC | ||||||
|---|---|---|---|---|---|---|
| Method | Min. | 1st Quartile | 2nd Quartile | 3rd Quartile | Max. | |
| Beam Data (Known disease status) | DBM | 0.73 (0.03) | 0.88 (0.02) | 0.91 (0.02) | 0.93 (0.02) | 0.97 (0.01) |
| Our Model | 0.79 (0.01) | 0.88 (0.01) | 0.89 (0.01) | 0.91 (0.01) | 0.93 (0.01) | |
| Estimated rater-specific AUC | ||||||||
|---|---|---|---|---|---|---|---|---|
| Method | 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
| Holmquist Data (Unknown disease status) | GRE | 0.87 (0.04) | 0.83 (0.05) | 0.89 (0.04) | 0.99 (0.01) | 0.86 (0.05) | 0.79 (0.05) | 0.95 (0.04) |
| FM | 0.94 (0.02) | 0.89 (0.03) | 0.90 (0.04) | 0.94 (0.03) | 0.93 (0.02) | 0.85 (0.03) | 1.00 (0.01) | |
| Our Model | 0.93 (0.02) | 0.91 (0.01) | 0.89 (0.01) | 0.89 (0.01) | 0.89 (0.01) | 0.85 (0.01) | 0.91 (0.01) | |