Сравнение методов

	Робастный анализ ROC	Робастный U-критерий Манна-Уитни
Область	Статистика	Статистика
Семейство	Hypothesis test	Hypothesis test
Год появления	1990s–2000s	1947 / 2003
Автор метода	Multiple contributors (Pepe, Qin, Zhou, and others)	Rand Wilcox (robust extensions); original test by Mann & Whitney (1947)
Тип	Robust diagnostic accuracy evaluation	Robust nonparametric two-group comparison
Основополагающий источник	Pepe, M. S. (2000). An interpretation for the ROC curve and inference using GLM procedures. Biometrics, 56(2), 352–359.	Wilcox, R. R. (2005). Introduction to Robust Estimation and Hypothesis Testing (2nd ed.). Academic Press. ISBN: 978-0127515427
Другие названия	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
Связанные	3	1
Сводка	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.