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Cohen's Kappa Formula:
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Cohen's Kappa (κ) is a statistical measure that calculates inter-rater reliability for categorical items. It accounts for agreement occurring by chance, providing a more accurate measure of agreement between raters than simple percentage agreement.
The calculator uses Cohen's Kappa formula:
Where:
Explanation: The formula calculates the proportion of agreement between raters after accounting for the agreement expected by chance alone.
Details: Inter-rater reliability is crucial in research and clinical settings to ensure consistency and objectivity in measurements, diagnoses, and coding across different observers or raters.
Tips: Enter observed agreement (Po) and expected agreement (Pe) as proportions between 0 and 1. Both values must be valid proportions within this range.
Q1: What does Cohen's Kappa value indicate?
A: Kappa values range from -1 to 1, where 1 indicates perfect agreement, 0 indicates agreement equivalent to chance, and negative values indicate agreement worse than chance.
Q2: How is Kappa interpreted?
A: Generally, κ < 0 = poor agreement, 0.01-0.20 = slight agreement, 0.21-0.40 = fair agreement, 0.41-0.60 = moderate agreement, 0.61-0.80 = substantial agreement, 0.81-1.00 = almost perfect agreement.
Q3: When should Cohen's Kappa be used?
A: Use Kappa when you have two raters assigning categorical ratings to the same set of items, and you want to measure agreement beyond chance.
Q4: What are the limitations of Cohen's Kappa?
A: Kappa can be affected by prevalence and bias, may not perform well with imbalanced data, and assumes independent ratings.
Q5: Are there alternatives to Cohen's Kappa?
A: Yes, alternatives include Fleiss' Kappa (for multiple raters), Intraclass Correlation Coefficient (for continuous data), and weighted Kappa (for ordinal data).