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Table 1 Model performance estimates for the base models

From: Modelling hospital outcome: problems with endogeneity

Model title Logit1 Logit2 Probit1 Probit2 Logit3 Probit3 LPM1 LPM2 LPM0
Regression method Logisitc Logit1 + site FE Probit Probit1 + site FE Logit 2 + RE Probit2+RE LPM_ldm LPM_ldm+siteFE  LPM[0,1]
Indices
 Number of patients 92,693 92,693 92,693 92,693 92,693 92,693 92,693 92,716 68,264
 Number of parameters 110 234 110 234 107 107 110 234 110
 ROC AUC 0.915 0.917 0.915 0.917 0.917 0.917 0.912 0.915 0.884
 H-L statistic; P-value 0.173 0.044 0.000 0.000 0.073 0.000 0.173 0.103 0.000
 Out-of-sample shrinkage % 0.940 1.600 0.940 0.580    0.390 0.360  
 In-sample-shrinkage % 0.380 0.360 0.380 −0.510    0.000 0.360  
 Overfitting % 0.560 1.250 0.560 1.090    0.390 0.000  
 Calibration belt: P-value 0.850 0.733 0.000 0.000 0.593 0.000 0.850 0.987 0.000
 AIC 33,867.39 33,712.31 33,897.66 33,756.53 33,758.82 33,799.85 33,863.39 33,712.31  
 BIC 34,792.25 35,665.78 34,803.62 35,710 34,674.21 34,715.24 34,769.35 35,665.78  
Development set
 CITL      −0.002 0.000    
 C-slope      1.005 1.009    
 AUC      0.917 0.915    
 E:O ratio      1.001 1.000    
Validation set
 CITL      0.002 0.021    
 C-slope      1.005 1.006    
 AUC      0.916 0.916    
 E:O ratio      0.989 0.987    
 ICC: unconditional      0.201 0.154    
 ICC: conditional      0.018 0.016    
 ICC: unconditional      0.201 0.154    
 ICC: conditional      0.018 0.016