How Robust Are Multirater Interrater Reliability Indices to Changes in Frequency Distribution?
Interrater reliability studies are used in a diverse set of fields. Often, these investigations involve three or more raters, and thus, require the use of indices such as Fleiss's kappa, Conger's kappa, or Krippendorff's alpha. Through two motivating examples-one theoretical and one f...
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Veröffentlicht in: | The American statistician 2016-11, Vol.70 (4), p.373-384 |
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description | Interrater reliability studies are used in a diverse set of fields. Often, these investigations involve three or more raters, and thus, require the use of indices such as Fleiss's kappa, Conger's kappa, or Krippendorff's alpha. Through two motivating examples-one theoretical and one from practice-this article exposes limitations of these indices when the units to be rated are not well-distributed across the rating categories. Then, using a Monte Carlo simulation and information visualizations, we argue for the use of two alternative indices, the Brennan-Prediger coefficient and Gwet's AC2, because the agreement levels reported by these indices are more robust to variation in the distribution of units that raters encounter. The article concludes by exploring the complex, interwoven relationship between the number of levels in a rating instrument, the agreement level present among raters, and the distribution of units that are to be scored. Supplementary materials for this article are available online. |
doi_str_mv | 10.1080/00031305.2016.1141708 |
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subjects | Agreement Conger Fleiss Frequency distribution Gwet Krippendorff Monte Carlo simulation Paradox Regression analysis Reliability Reliability analysis Robustness Statistical methods STATISTICAL PRACTICE Statistics |
title | How Robust Are Multirater Interrater Reliability Indices to Changes in Frequency Distribution? |
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