Methoden vergleichen

	Cohens Kappa-Koeffizient	Fleiss' Kappa für die Übereinstimmung mehrerer Beurteiler	McNemar-Test
Fachgebiet	Statistik	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test	Hypothesis test
Entstehungsjahr	1960	1971	1947
Urheber	Jacob Cohen	Joseph L. Fleiss	Quinn McNemar
Typ	Inter-rater reliability coefficient	Non-parametric agreement measure	Nonparametric test for paired binary data
Wegweisende Quelle	Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1), 37–46.	Fleiss, J.L. (1971). Measuring Nominal Scale Agreement Among Many Raters. Psychological Bulletin, 76(5), 378–382.	McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153–157.
Aliasnamen	kappa coefficient, kappa statistic, Cohen's Kappa (Değerlendiriciler Arası Uyum)	multi-rater kappa, Fleiss kappa, Fleiss' Kappa (Çoklu Değerlendirici Uyumu)	McNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi
Verwandt	3	2	5
Zusammenfassung	Cohen's kappa (κ) is a statistical measure of inter-rater reliability for categorical classifications, introduced by Jacob Cohen in 1960. Unlike simple percent agreement, kappa corrects for the level of agreement that would be expected purely by chance, making it the standard metric when two raters independently assign observations to the same set of mutually exclusive categories.	Fleiss' Kappa is a non-parametric statistic for measuring the degree of agreement among three or more raters who classify items into mutually exclusive nominal categories. Introduced by Joseph L. Fleiss in 1971 as a generalization of Cohen's Kappa beyond two raters, it corrects observed agreement for the level of agreement expected by chance alone, making it the standard reliability index in medical diagnosis studies, content analysis, and multi-coder research.	McNemar's test is a nonparametric hypothesis test that compares two paired (correlated) binary proportions, such as a yes/no measurement taken on the same subjects before and after an intervention. It was introduced by Quinn McNemar in 1947 and works on the 2×2 table of matched outcomes.