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| Analyse ROC Robuste× | Robust Mann-Whitney U test× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1990s–2000s | 1947 / 2003 |
| Auteur d'origine≠ | Multiple contributors (Pepe, Qin, Zhou, and others) | Rand Wilcox (robust extensions); original test by Mann & Whitney (1947) |
| Type≠ | Robust diagnostic accuracy evaluation | Robust nonparametric two-group comparison |
| Source fondatrice≠ | Pepe, M. S. (2000). An interpretation for the ROC curve and inference using GLM procedures. Biometrics, 56(2), 352–359. DOI ↗ | Wilcox, R. R. (2005). Introduction to Robust Estimation and Hypothesis Testing (2nd ed.). Academic Press. ISBN: 978-0127515427 |
| Alias | robust AUC analysis, outlier-resistant ROC, robust diagnostic accuracy analysis, robust sensitivity-specificity analysis | robust Wilcoxon rank-sum test, robust two-sample rank test, outlier-resistant Mann-Whitney test, robust nonparametric two-group comparison |
| Apparentées≠ | 3 | 1 |
| Résumé≠ | Robust ROC analysis evaluates the diagnostic accuracy of a continuous or ordinal biomarker in distinguishing between two groups (e.g., diseased vs. healthy) while protecting against the distorting effects of outliers, non-normality, or distributional violations that can bias standard parametric ROC estimates and AUC confidence intervals. | The Robust Mann-Whitney U test is a nonparametric two-group comparison that combines the rank-based logic of the classic Mann-Whitney U test with modern robust techniques — such as outlier screening, trimmed means, or robust variance estimation — to produce reliable inferences when data contain extreme values, heavy-tailed distributions, or other violations that compromise the standard test. |
| ScholarGateJeu de données ↗ |
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