1. What is Cohen's Kappa?

Cohen's Kappa (κ) is a statistical measure that calculates interrater reliability for qualitative items. It accounts for the possibility of agreement occurring by chance, providing a more accurate measure of agreement between raters than simple percentage agreement.

2. How Does the Calculator Work?

The calculator uses Cohen's Kappa equation:

Where:

• \( PA \) — Observed agreement between raters (fraction)
• \( PE \) — Expected agreement by chance (fraction)

Explanation: The equation measures the agreement between two raters beyond what would be expected by chance alone, with values ranging from -1 to 1.

3. Importance of Interrater Reliability

Details: Interrater reliability is crucial in research and clinical settings to ensure consistency and objectivity in measurements, diagnoses, and assessments across different observers or raters.

4. Using the Calculator

Tips: Enter observed agreement (PA) and expected agreement (PE) as fractions between 0 and 1. PE must be less than 1 for valid calculation.

5. Frequently Asked Questions (FAQ)

Q1: What do different kappa values mean?
A: Values ≤0 indicate no agreement, 0.01-0.20 slight, 0.21-0.40 fair, 0.41-0.60 moderate, 0.61-0.80 substantial, and 0.81-1.00 almost perfect agreement.

Q2: When should Cohen's Kappa be used?
A: It's appropriate for categorical data when two raters each classify items into mutually exclusive categories.

Q3: What are the limitations of Cohen's Kappa?
A: It can be affected by prevalence and bias, and may not be suitable for ordinal data or more than two raters.

Q4: How is expected agreement calculated?
A: PE is typically calculated from the marginal probabilities of each rater's classifications using the formula for chance agreement.

Q5: Are there alternatives to Cohen's Kappa?
A: Yes, including weighted kappa for ordinal data, Fleiss' kappa for multiple raters, and intraclass correlation coefficient for continuous data.