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| Robust ROC 분석× | 강건한 Mann-Whitney U 검정× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1990s–2000s | 1947 / 2003 |
| 창시자≠ | Multiple contributors (Pepe, Qin, Zhou, and others) | Rand Wilcox (robust extensions); original test by Mann & Whitney (1947) |
| 유형≠ | Robust diagnostic accuracy evaluation | Robust nonparametric two-group comparison |
| 원전≠ | 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 |
| 별칭 | 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 |
| 관련≠ | 3 | 1 |
| 요약≠ | 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. |
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