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Table 6 Accuracy parameters of the logistic regression models

From: Determination of puberty in gilts: contrast of diagnostic methods

Model Parameter
Nagelkerke’s R2 Sensitivity (95%IC) Specificity (95%IC) Positive predictive value (95%IC) Negative
predictive value (95%IC)
Area under the ROC curve (95%IC)
I 0.520 0.844 (0.738; 0.950) 0.792 (0.629; 0.954) 0.883 (0.787; 0.979) 0.731 (0.561; 0.901) 0.882 (0.806; 0.959)
II 0.722 0.867 (0.767; 0.966) 0.875 (0.743; 1.000) 0.928 (0.850; 1.000) 0.778 (0.621; 0.935) 0.943 (0.890; 0.996)
III 0.846 0.956 (0.897; 1.000) 0.958 (0.878; 1.000) 0.978 (0.935; 1.000) 0.920 (0.814; 1.000) 0.957 (0.900; 1.000)
IV 0.834 0.933 (0.860; 1.000) 0.958 (0.878; 1.000) 0.977 (0.932; 1.000) 0.885 (0.764; 1.000) 0.972 (0.937; 1.000)
V 0.780 0.955 (0.895; 1.000) 0.826 (0.671; 0.981) 0.915 (0.835; 0.995) 0.905 (0.780; 1.000) 0.970 (0.933; 1.000)
VI 0.746 0.891 (0.801; 0.981) 0.958 (0.878; 1.000) 0.976 (0.929; 1.000) 0.821 (0.680; 0.962) 0.925 (0.854; 0.996)
VII 0.442 0.804 (0.690; 0.919) 0.826 (0.671; 0.981) 0.902 (0.812; 0.992) 0.678 (0.506; 0.850) 0.815 (0.703; 0.897)