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It should be possible to calculate the significance of a single ROC curve.
This would test H_0: AUC = 0.5.
For a full AUC this should correspond to the Wilcoxon Test. For partial AUC we need to use bootstrapping. Something like this:
roc.test(roc(aSAH$outcome, aSAH$ndka)) roc.test(roc(aSAH$outcome, aSAH$ndka, partial.auc = c(1, 0.9)))
The text was updated successfully, but these errors were encountered:
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It should be possible to calculate the significance of a single ROC curve.
This would test H_0: AUC = 0.5.
For a full AUC this should correspond to the Wilcoxon Test. For partial AUC we need to use bootstrapping. Something like this:
The text was updated successfully, but these errors were encountered: