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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.
In statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon.
Jacob Cohen (April 20, 1923 – January 20, 1998) was an American psychologist and statistician best known for his work on statistical power and effect size, which helped to lay foundations for current statistical meta-analysis [1] [2] and the methods of estimation statistics. He gave his name to such measures as Cohen's kappa, Cohen's d, and ...
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.
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The concordance correlation coefficient is nearly identical to some of the measures called intra-class correlations.Comparisons of the concordance correlation coefficient with an "ordinary" intraclass correlation on different data sets found only small differences between the two correlations, in one case on the third decimal. [2]
Krippendorff's alpha coefficient, [1] named after academic Klaus Krippendorff, is a statistical measure of the agreement achieved when coding a set of units of analysis.. Since the 1970s, alpha has been used in content analysis where textual units are categorized by trained readers, in counseling and survey research where experts code open-ended interview data into analyzable terms, in ...
Cicchetti (1994) [19] gives the following often quoted guidelines for interpretation for kappa or ICC inter-rater agreement measures: Less than 0.40—poor. Between 0.40 and 0.59—fair. Between 0.60 and 0.74—good. Between 0.75 and 1.00—excellent. A different guideline is given by Koo and Li (2016): [20] below 0.50: poor; between 0.50 and 0 ...