Table 1.

Prediction results for simulation setting 1

	Prediction
Method	Sensitivity	Specificity	Accuracy	AUC
LASSO	0.63(0.05)	0.62(0.04)	0.62(0.02)	0.66(0.02)
Enet	0.65(0.05)	0.64(0.05)	0.63(0.02)	0.68(0.02)
Network	0.82(0.06)	0.82(0.06)	0.81(0.05)	0.89(0.05)
Abs-Network	0.82(0.05)	0.82(0.06)	0.81(0.04)	0.89(0.04)
Merge-LASSO	0.65(0.04)	0.65(0.06)	0.63(0.02)	0.68(0.02)
Merge-Enet	0.65(0.05)	0.64(0.05)	0.63(0.02)	0.68(0.02)
Merge-Network	0.87(0.04)	0.88(0.03)	0.88(0.03)	0.95(0.02)
Merge-Abs-Network	0.88(0.04)	0.88(0.03)	0.88(0.02)	0.95(0.02)
Int-LASSO	0.88(0.02)	0.88(0.02)	0.88(0.02)	0.96(0.01)
Int-Enet	0.88(0.02)	0.88(0.02)	0.88(0.02)	0.96(0.01)
Int-Network	0.89(0.02)	0.90(0.02)	0.89(0.01)	0.96(0.01)
Int-Abs-Network	0.90(0.02)	0.90(0.02)	0.90(0.01)	0.97(0.01)
MetaLasso	0.75(0.05)	0.76(0.04)	0.76(0.04)	0.84(0.04)

β is shown in (9), $\left({\overline{\beta }}_0^1,{\overline{\beta }}_0^2,{\overline{\beta }}_0^3,{\overline{\beta }}_0^4\right)=(-3,-1,1,3)$

The maximum value for each measure is highlighted using boldface font