ROC curve (TTE vs. MIF vs. Logistic Model)

MIF compare with TTE, AUC increased from 0.75 to 0.77, p-value=0.9047. Logistic model compare with TTE, AUC increased from 0.75 to 0.91, p-value=0.1798.

Quick Rule 0: Event if TTE > 50

## sensitivity specificity         ppv         npv 
##   0.5384615   0.9230769   0.7777778   0.8000000

Quick Rule 1.0: Event if MIF > 60

## sensitivity specificity         ppv         npv 
##   0.6153846   1.0000000   1.0000000   0.8387097

Quick Rule 1.1: Event if MIF > 50

## sensitivity specificity         ppv         npv 
##   0.6153846   0.9230769   0.8000000   0.8275862

Quick Rule 1.2: Event if MIF > 45

## sensitivity specificity         ppv         npv 
##   0.6153846   0.8461538   0.6666667   0.8148148

Quick Rule 1.3: Event if MIF > 40

## sensitivity specificity         ppv         npv 
##   0.6923077   0.7692308   0.6000000   0.8333333

Quick Rule 2.0: Event if MIF > 60 or TTE > 50

## sensitivity specificity         ppv         npv 
##   0.9230769   0.9230769   0.8571429   0.9600000

Quick Rule 2.1: Event if MIF > 50 or TTE > 50

## sensitivity specificity         ppv         npv 
##   0.9230769   0.8461538   0.7500000   0.9565217

Quick Rule 2.2: Event if MIF > 45 or TTE > 50

## sensitivity specificity         ppv         npv 
##   0.9230769   0.8076923   0.7058824   0.9545455

Quick Rule 2.3: Event if MIF > 40 or TTE > 50

## sensitivity specificity         ppv         npv 
##   0.9230769   0.7307692   0.6315789   0.9500000

Quick Rule 3: Event if .4*MIF + .6*TTE > 50

## sensitivity specificity         ppv         npv 
##   0.6153846   0.9230769   0.8000000   0.8275862