Table 2:
Simulation results for logistic regression with sample size 200. CE: classification error (number of incorrect classification); TP: true positive; FP: false positive; number of Type 1 true network markers: 22; number of Type 2 true network markers: 12.
| Method | CE | TP | FP | AUC | CE | TP | FP | AUC |
|---|---|---|---|---|---|---|---|---|
| Type 1 p = 33 | Type 1 p = 110 | |||||||
| Lasso | 20.8(0.7) | 21.2(0.1) | 6.9(0.4) | 0.811(0.004) | 30.8(1.1) | 19.1(0.4) | 25.1(1.7) | 0.836(0.004) |
| Elastic-net | 21.0(0.8) | 21.4(0.1) | 8.4(0.4) | 0.818(0.004) | 32.6(0.8) | 19.9(0.2) | 29.4(2.1) | 0.848(0.003) |
| Ising(b=5) | 39.2(3.0) | 15.2(1.2) | 0.0(0.0) | 0.937(0.011) | 47.6(4.1) | 13.5(1.1) | 10.2(2.9) | 0.826(0.031) |
| TGLG-I | 19.2(0.6) | 21.9(0.1) | 10.0(0.2) | 0.877(0.011) | 30.5(0.9) | 17.1(0.3) | 16.0(1.4) | 0.851(0.008) |
| TGLG-F | 19.4(0.7) | 21.8(0.1) | 8.0(0.5) | 0.858(0.021) | 30.8(1.1) | 17.6(0.4) | 13.0(1.1) | 0.870(0.007) |
| TGLG-L | 18.7(0.7) | 21.8(0.1) | 7.5(0.5) | 0.875(0.018) | 30.4(1.0) | 17.3(0.3) | 13.4(1.1) | 0.858(0.008) |
| Type 2 p = 33 | Type 2 p = 110 | |||||||
| Lasso | 25.2(0.9) | 11.7(0.1) | 10.1(0.7) | 0.856(0.004) | 32.7(1.0) | 10.6(0.2) | 22.7(2.2) | 0.872(0.004) |
| Elastic-net | 26.1(0.8) | 11.9(0.0) | 13.2(0.7) | 0.796(0.004) | 36.6(1.2) | 10.5(0.3) | 25.9(2.5) | 0.849(0.004) |
| Ising(b=5) | 27.4(1.4) | 9.5(0.4) | 7.2(0.4) | 0.899(0.016) | 37.7(2.8) | 7.4(0.5) | 9.0(1.7) | 0.820(0.025) |
| TGLG-I | 22.6(0.8) | 11.4(0.1) | 4.8(0.6) | 0.961(0.007) | 29.4(1.2) | 9.7(0.3) | 6.9(0.9) | 0.897(0.0012) |
| TGLG-F | 23.2(0.8) | 11.5(0.1) | 6.3(0.6) | 0.941(0.010) | 29.3(1.0) | 9.9(0.3) | 6.7(0.6) | 0.903(0.010) |
| TGLG-L | 22.1(0.8) | 11.6(0.1) | 5.8(0.7) | 0.959(0.005) | 28.6(1.0) | 10.1(0.2) | 6.2(0.8) | 0.921(0.009) |