1. What Is Cohen's Kappa?

Cohen's Kappa (κ) is a statistical measure of inter-rater agreement for categorical items. It accounts for agreement occurring by chance, providing a more robust measure than simple percentage agreement.

2. How Does The Calculator Work?

The calculator uses Cohen's Kappa formula:

Where:

• \( p_o \) — Observed agreement proportion
• \( p_e \) — Expected agreement proportion by chance
• \( \kappa \) — Cohen's Kappa coefficient (0-1)

Explanation: The formula subtracts chance agreement from observed agreement and normalizes by the maximum possible improvement over chance.

3. Importance Of Inter-Rater Agreement

Details: Cohen's Kappa is essential in research, medicine, and social sciences to ensure reliability of categorical measurements between different raters or instruments.

4. Using The Calculator

Tips: Enter observed agreement (pₒ) and expected agreement (pₑ) as proportions between 0 and 1. Both values must be valid proportions and pₑ cannot equal 1.

5. Frequently Asked Questions (FAQ)

Q1: What Do Different Kappa Values Mean?
A: <0 = Poor agreement, 0-0.20 = Slight, 0.21-0.40 = Fair, 0.41-0.60 = Moderate, 0.61-0.80 = Substantial, 0.81-1.00 = Almost perfect agreement.

Q2: How Is Expected Agreement Calculated?
A: pₑ is calculated from marginal probabilities: pₑ = Σ(marginal probability of category i for rater 1 × marginal probability of category i for rater 2).

Q3: When Should Cohen's Kappa Be Used?
A: Use for nominal or ordinal data with two raters. For more than two raters, consider Fleiss' Kappa or intraclass correlation.

Q4: What Are The Limitations Of Cohen's Kappa?
A: Affected by prevalence and bias, may be misleading with skewed marginal distributions. Consider prevalence-adjusted indices if needed.

Q5: How Does Kappa Differ From Percentage Agreement?
A: Percentage agreement ignores chance agreement, while Kappa accounts for it, making it more robust for comparing different studies.