An intraclass correlation coefficient (ICC) is used to determine if items or subjects can be rated reliably by different raters.

The value of an ICC can range from 0 to 1, with 0 indicating no reliability among raters and 1 indicating perfect reliability.

The easiest way to calculate ICC in R is to use the **icc()** function from the **irr** package, which uses the following syntax:

**icc(ratings, model, type, unit)**

where:

**ratings:**A dataframe or matrix of ratings**model:**The type of model to use. Options include “oneway” or “twoway”**type:**The type of relationship to calculate between raters. Options include “consistency” or “agreement”**unit:**The unit of analysis. Options include “single” or “average”

This tutorial provides an example of how to use this function in practice.

**Step 1: Create the Data**

Suppose four different judges were asked to rate the quality of 10 different college entrance exams. We can create the following dataframe to holding the ratings of the judges:

#create data data <- data.frame(A=c(1, 1, 3, 6, 6, 7, 8, 9, 8, 7), B=c(2, 3, 8, 4, 5, 5, 7, 9, 8, 8), C=c(0, 4, 1, 5, 5, 6, 6, 9, 8, 8), D=c(1, 2, 3, 3, 6, 4, 6, 8, 8, 9))

**Step 2: Calculate the Intraclass Correlation Coefficient**

Suppose the four judges were randomly selected from a population of qualified entrance exam judges and that we’d like to measure the absolute agreement among judges and that we’re interested in using the ratings from a single rater perspective as the basis for our measurement.

We can use the following code in R to fit a **two-way model**, using **absolute agreement** as the relationship among raters, and using **single** as our unit of interest:

#load the interrater reliability package library(irr) #define data data <- data.frame(A=c(1, 1, 3, 6, 6, 7, 8, 9, 8, 7), B=c(2, 3, 8, 4, 5, 5, 7, 9, 8, 8), C=c(0, 4, 1, 5, 5, 6, 6, 9, 8, 8), D=c(1, 2, 3, 3, 6, 4, 6, 8, 8, 9)) #calculate ICC icc(data, model = "twoway", type = "agreement", unit = "single") Model: twoway Type : agreement Subjects = 10 Raters = 4 ICC(A,1) = 0.782 F-Test, H0: r0 = 0 ; H1: r0 > 0 F(9,30) = 15.3 , p = 5.93e-09 95%-Confidence Interval for ICC Population Values: 0.554 < ICC < 0.931

The intraclass correlation coefficient (ICC) turns out to be **0.782**.

Here is how to interpret the value of an intraclass correlation coefficient, according to Koo & Li:

**Less than 0.50:**Poor reliability**Between 0.5 and 0.75:**Moderate reliability**Between 0.75 and 0.9:**Good reliability**Greater than 0.9:**Excellent reliability

Thus, we would conclude that an ICC of **0.782** indicates that the exams can be rated with “good” reliability by different raters.

**A Note on Calculating ICC**

There are several different versions of an ICC that can be calculated, depending on the following three factors:

**Model:**One-Way Random Effects, Two-Way Random Effects, or Two-Way Mixed Effects**Type of Relationship:**Consistency or Absolute Agreement**Unit:**Single rater or the mean of raters

In the previous example, the ICC that we calculated used the following assumptions:

**Model:**Two-Way Random Effects**Type of Relationship:**Absolute Agreement**Unit:**Single rater

For a detailed explanation of these assumptions, please refer to this article.