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Cohen's Kappa Formula:
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Cohen's Kappa (κ) is a statistical measure that calculates inter-rater agreement for categorical items. It accounts for the possibility of agreement occurring by chance, providing a more accurate measure of agreement than simple percentage agreement.
The calculator uses Cohen's Kappa formula:
Where:
Explanation: The formula subtracts the expected agreement (chance agreement) from the observed agreement and normalizes it by the maximum possible improvement over chance.
Details: Cohen's Kappa is widely used in research, psychology, medicine, and social sciences to measure agreement between two raters or methods. It helps determine the reliability of categorical measurements and diagnostic tests.
Tips: Enter observed agreement proportion (Po) and expected agreement proportion (Pe) as values between 0 and 1. Both values must be valid proportions (0 ≤ Po ≤ 1, 0 ≤ Pe < 1).
Q1: What does the 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 to interpret Kappa values?
A: Generally: <0 = Poor, 0.01-0.20 = Slight, 0.21-0.40 = Fair, 0.41-0.60 = Moderate, 0.61-0.80 = Substantial, 0.81-1.00 = Almost perfect agreement.
Q3: When should Cohen's Kappa be used?
A: Use when measuring agreement between two raters on categorical data, especially in reliability studies, diagnostic test evaluation, and inter-rater reliability assessments.
Q4: What are the limitations of Cohen's Kappa?
A: Kappa can be affected by prevalence and bias, may not perform well with imbalanced categories, and assumes that raters are independent.
Q5: Are there alternatives to Cohen's Kappa?
A: Yes, alternatives include weighted Kappa (for ordinal data), Fleiss' Kappa (for multiple raters), and intraclass correlation coefficient for continuous data.