Connie Rees

106 The model's discriminative ability was assessed using the ROC curve, and the resulting AUC was 0.831 (95%CI 0.761 – 0.901) (see Figure 4). The Nagelkerke’s R square for the overall performance of the model was 0.682. As for calibration, the Hosmer-Lemeshow goodness-of-fit test did not show significance (chi-square 4.398, p = 0.820). Figure 4.4. ROC-curve external validation. ROC-curve. The diagonal is the reference line, indicating an AUC of 0.50. A value less than 0.50 indicates the model is no better than random prediction. A value of 1.0 indicates perfect prediction. The AUC curve for this model was calculated at 0.831.

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