1. What is ICC?

The Intraclass Correlation Coefficient (ICC) measures the reliability of ratings or measurements for clustered data. It assesses how strongly units in the same group resemble each other.

2. How Does the Calculator Work?

The calculator uses the ICC formula:

Where:

• \( MS_{between} \) — Mean square between groups (variance between subjects)
• \( MS_{error} \) — Mean square error (variance within subjects)
• \( k \) — Number of raters or measurements

Explanation: The equation compares the between-group variance to the total variance, with adjustment for the number of raters.

3. Importance of ICC Calculation

Details: ICC is crucial for assessing inter-rater reliability in research studies, clinical assessments, and any situation requiring consistency between multiple raters or measurements.

4. Using the Calculator

Tips: Enter the mean square between groups, mean square error, and number of raters. All values must be positive numbers with at least 2 raters.

5. Frequently Asked Questions (FAQ)

Q1: What is a good ICC value?
A: ICC > 0.75 indicates excellent reliability, 0.60-0.74 good, 0.40-0.59 fair, and <0.40 poor reliability.

Q2: What's the difference between ICC and Pearson correlation?
A: ICC assesses absolute agreement while Pearson assesses linear relationship. ICC is more appropriate for reliability studies.

Q3: Which ICC formula should I use?
A: This calculator uses ICC(1,1) or ICC(2,1) depending on your study design. Consult a statistician for complex designs.

Q4: Can ICC be negative?
A: Yes, but it indicates more variation within subjects than between them, suggesting very poor reliability.

Q5: How many raters do I need?
A: Typically 2-5 raters are used. More raters increase reliability but also study complexity and cost.