Fig. 2

The Bayesian models outperformed the standard logistic regression model based on the MSE criterion. Mean squared error (MSE) for four different methods are shown for different scenarios of sensitivity (SN) and specificity (SP) [SN = 0.6 and SP = 0.9 (upper left panel); SN = 0.9 and SP = 0.9 (upper right panel); SN = 0.6 and SP = 0.98 (lower left panel); SN = 0.9 and SP = 0.98 (lower right panel)]. These results are based on 100 simulated datasets, with 2000 individuals in each dataset. Smaller values indicate better performance