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| Gwet's AC1× | Krippendorff's Alpha× | |
|---|---|---|
| Fagområde | Communication | Communication |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 2008 | 1970 |
| Ophavsperson≠ | Kilem L. Gwet | Klaus Krippendorff |
| Type≠ | Chance-corrected agreement coefficient robust to the prevalence paradox | Chance-corrected reliability coefficient for coded data |
| Oprindelig kilde≠ | Gwet, K. L. (2008). Computing inter-rater reliability and its variance in the presence of high agreement. British Journal of Mathematical and Statistical Psychology, 61(1), 29–48. DOI ↗ | Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1(1), 77–89. DOI ↗ |
| Aliasser | Gwet AC1, AC1 coefficient, Gwet's first-order agreement coefficient, Gwet AC1 Katsayısı | Krippendorff alpha, K-alpha, Alpha reliability coefficient, Krippendorff Alfa Katsayısı |
| Relaterede | 4 | 4 |
| Resumé≠ | Gwet's AC1 is a chance-corrected agreement coefficient introduced by Kilem Gwet in 2008 as a robust alternative to Cohen's and Fleiss' kappa. It targets the kappa paradox — the unsettling result where coders agree on the vast majority of units yet kappa is near zero because one category dominates — by estimating chance agreement in a way that does not collapse when category prevalence is extreme. | Krippendorff's alpha is a chance-corrected coefficient that quantifies the reliability of coding decisions made by two or more observers, and is the standard reliability statistic in communication content analysis. Unlike percent agreement, it corrects for the agreement expected by chance; unlike Cohen's kappa, it generalizes seamlessly to any number of coders, any measurement level (nominal, ordinal, interval, ratio), and data sets with missing values. |
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