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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.
Bennett et al. suggested adjusting inter-rater reliability to accommodate the percentage of rater agreement that might be expected by chance was a better measure than simple agreement between raters. [2] They proposed an index which adjusted the proportion of rater agreement based on the number of categories employed.
These rules help the WUSCT to have a higher inter-rater reliability and also increase the overall reliability of the test. If the test was taken on pen-and-paper, the responses should be typed up and any identifying information is deleted to protect the subject's privacy and to prevent identifying information from coloring the rater's scores.
Cohen's kappa coefficient (κ, lowercase Greek kappa) is a statistic that is used to measure inter-rater reliability (and also intra-rater reliability) for qualitative (categorical) items. [1] It is generally thought to be a more robust measure than simple percent agreement calculation, as κ takes into account the possibility of the agreement ...
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]
Scott's pi (named after William A Scott) is a statistic for measuring inter-rater reliability for nominal data in communication studies.Textual entities are annotated with categories by different annotators, and various measures are used to assess the extent of agreement between the annotators, one of which is Scott's pi.
Inter-rater reliability assesses the degree of agreement between two or more raters in their appraisals. For example, a person gets a stomach ache and different doctors all give the same diagnosis. For example, a person gets a stomach ache and different doctors all give the same diagnosis.
Kendall's W (also known as Kendall's coefficient of concordance) is a non-parametric statistic for rank correlation.It is a normalization of the statistic of the Friedman test, and can be used for assessing agreement among raters and in particular inter-rater reliability.