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Fleiss' kappa is a generalisation of Scott's pi statistic, [2] a statistical measure of inter-rater reliability. [3] It is also related to Cohen's kappa statistic and Youden's J statistic which may be more appropriate in certain instances. [4]
Different statistics are appropriate for different types of measurement. Some options are joint-probability of agreement, such as Cohen's kappa, Scott's pi and Fleiss' kappa; or inter-rater correlation, concordance correlation coefficient, intra-class correlation, and Krippendorff's alpha.
Cohen's kappa measures the agreement between two raters who each classify N items into C mutually exclusive categories. The definition of is =, where p o is the relative observed agreement among raters, and p e is the hypothetical probability of chance agreement, using the observed data to calculate the probabilities of each observer randomly selecting each category.
Indeed, Cohen's kappa explicitly ignores all systematic, average disagreement between the annotators prior to comparing the annotators. So Cohen's kappa assesses only the level of randomly varying disagreements between the annotators, not systematic, average disagreements. Scott's pi is extended to more than two annotators by Fleiss' kappa.
AgreeStat 360: cloud-based inter-rater reliability analysis, Cohen's kappa, Gwet's AC1/AC2, Krippendorff's alpha, Brennan-Prediger, Fleiss generalized kappa, intraclass correlation coefficients; A useful online tool that allows calculation of the different types of ICC
Kappa statistics such as Cohen's kappa [6] [7] and Fleiss' kappa are methods for calculating inter-rater reliability. Physics. In cosmology, the Einstein gravitational constant is denoted by κ. [8] In physics, the torsional constant of an oscillator is given by κ. [9] In physics, the coupling coefficient in magnetostatics is represented by κ ...
Fleiss' kappa, like F-score, assumes that both variables are drawn from the same distribution and thus have the same expected prevalence, while Cohen's kappa assumes that the variables are drawn from distinct distributions and referenced to a model of expectation that assumes prevalences are independent. [8]
Fleiss' kappa; Goodman and Kruskal's lambda; Guilford’s G; Gwet's AC1; Hanssen–Kuipers discriminant; Heidke skill score; Jaccard index; Janson and Vegelius' C; Kappa statistics; Klecka's tau; Krippendorff's Alpha; Kuipers performance index; Matthews correlation coefficient; Phi coefficient; Press' Q; Renkonen similarity index; Prevalence ...