Shown in the app as roc_auc. Part of the method reference, under Diagnostic accuracy and agreement.
When to use
How well a CONTINUOUS score/marker discriminates a BINARY gold-standard outcome: the ROC curve, area under the curve (AUC) with a DeLong confidence interval, and the Youden-optimal cutoff with its sensitivity/specificity.
What you provide
- Reference standard (the true condition): one two-level column.
- Score (the continuous marker): one numeric column.
Options
Missing data
- Complete case (listwise deletion)
Multiple comparisons
- Not adjustable for this method. Where it makes post-hoc comparisons, the procedure applies its own correction.
Confidence level
Every interval in the result is reported at the level you choose:
Other methods under Diagnostic accuracy and agreement:
Worked examples
Celeus's result on a published or illustrative dataset, next to an independent computation and, where one exists, a published value. The data themselves are not reproduced here.
pROC::aSAH
- Source: Published dataset distributed with an R package
- Licence: pROC (GPL >= 3)
- Reference: Turck N et al. (2010), Intensive Care Medicine 36(1):107-115; the aSAH dataset as distributed with the pROC package (Robin et al. 2011, BMC Bioinformatics 12:77)
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Area under the ROC curve | 0.731369 | 0.731369 | - | Yes |
|---|
pROC::aSAH (outcome relabelled case/control)
- Source: Published dataset distributed with an R package
- Licence: pROC (GPL >= 3)
- Reference: Turck N et al. (2010), Intensive Care Medicine 36(1):107-115; the aSAH dataset as distributed with the pROC package, its outcome relabelled Poor = case, Good = control, and the positive value chosen as case
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Area under the ROC curve | 0.731369 | 0.731369 | - | Yes |
|---|
| Sensitivity | 0.634146 | 0.634146 | - | Yes |
|---|
| Specificity | 0.805556 | 0.805556 | - | Yes |
|---|
pROC::aSAH (category order Poor, Good; higher scores positive)
- Source: Published dataset distributed with an R package
- Licence: pROC (GPL >= 3)
- Reference: Turck N et al. (2010), Intensive Care Medicine 36(1):107-115; the aSAH dataset as distributed with the pROC package, with Good ordered last (so positive) and the direction fixed to higher scores
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Area under the ROC curve | 0.268631 | 0.268631 | - | Yes |
|---|
pROC::aSAH (s100b, 90% interval)
- Source: Published dataset distributed with an R package
- Licence: pROC (GPL >= 3)
- Reference: Turck N et al. (2010), Intensive Care Medicine 36(1):107-115; the aSAH dataset as distributed with the pROC package
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Confidence interval for the area under the ROC curve | 0.646397, 0.816341 | 0.646397, 0.816341 | - | Yes |
|---|
pROC::aSAH (s100b, 99% interval)
- Source: Published dataset distributed with an R package
- Licence: pROC (GPL >= 3)
- Reference: Turck N et al. (2010), Intensive Care Medicine 36(1):107-115; the aSAH dataset as distributed with the pROC package
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Confidence interval for the area under the ROC curve | 0.598303, 0.864434 | 0.598303, 0.864434 | - | Yes |
|---|
pROC::aSAH (WFNS grade as an ordinal score, heavily tied)
- Source: Published dataset distributed with an R package
- Licence: pROC (GPL >= 3)
- Reference: Turck N et al. (2010), Intensive Care Medicine 36(1):107-115; the aSAH dataset as distributed with the pROC package
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Area under the ROC curve | 0.823679 | 0.823679 | - | Yes |
|---|
synthetic example (6 rows, a perfectly separating score)
- Source: Illustrative or synthetic example data
- Licence: n/a (synthetic data written for this check, not sourced)
- Reference: Hand-authored synthetic fixture, not sourced or published data; the score separates the two groups completely, so no AUC interval is reported.
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Area under the ROC curve | 1 | 1 | - | Yes |
|---|
carData::GSSvocab (vocabulary score vs native birth)
- Source: Published dataset distributed with an R package
- Licence: carData (GPL)
- Reference: General Social Survey extract, from Fox & Weisberg, An R Companion to Applied Regression (carData)
| Quantity | Celeus | Independent computation | Published value | Agrees |
|---|
| Area under the ROC curve | 0.60761 | 0.60761 | - | Yes |
|---|
| Number of observations | 27470 | 27470 | - | Yes |
|---|
Validation report
References
- Hanley, J. A., McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143: 29-36. doi:10.1148/radiology.143.1.7063747 doi:10.1148/radiology.143.1.7063747
- DeLong, E. R., DeLong, D. M., Clarke-Pearson, D. L. (1988). Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44: 837-845. doi:10.2307/2531595 doi:10.2307/2531595