1. What is Cohen's Kappa?

Definition: Cohen's Kappa is a statistic that measures inter-rater agreement for qualitative (categorical) items.

Purpose: It's commonly used in research to assess the agreement between two raters while accounting for agreement that occurs by chance.

2. How Does the Calculator Work?

The calculator uses the formula:

Where:

• \( \kappa \) — Cohen's Kappa coefficient (ranges from -1 to 1)
• \( P_o \) — Observed agreement between raters (0 to 1)
• \( P_e \) — Expected agreement by chance (0 to 1)

Interpretation:

• κ ≤ 0: No agreement
• 0 < κ ≤ 0.20: Slight agreement
• 0.20 < κ ≤ 0.40: Fair agreement
• 0.40 < κ ≤ 0.60: Moderate agreement
• 0.60 < κ ≤ 0.80: Substantial agreement
• 0.80 < κ ≤ 1: Almost perfect agreement

3. Importance of Cohen's Kappa

Details: Unlike simple percent agreement, Cohen's Kappa accounts for agreement occurring by chance, providing a more reliable measure of inter-rater reliability.

4. Using the Calculator

Tips: Enter the observed agreement (Po) and expected agreement (Pe) as values between 0 and 1. Pe must be less than 1.

5. Frequently Asked Questions (FAQ)

Q1: What's a good Kappa value?
A: Generally, κ > 0.60 is considered acceptable, but this depends on your field. Values above 0.80 are excellent.

Q2: How do I calculate Po and Pe?
A: Po is the proportion of observed agreement. Pe is calculated based on the marginal probabilities of each rater's classifications.

Q3: Can Kappa be negative?
A: Yes, negative values indicate agreement worse than chance, though this is rare in practice.

Q4: What's the difference between Kappa and percent agreement?
A: Percent agreement doesn't account for chance agreement, while Kappa does, making it more robust.

Q5: When should I use Cohen's Kappa?
A: Use it when assessing agreement between two raters on categorical data with the same categories.