How to Calculate Inter Rater Agreement

Inter-rater agreement is the degree to which two or more raters or evaluators who are assessing the same set of data, agree with each other. This is a very important concept in research and quality control, as it helps to ensure that the results obtained are reliable and consistent across different raters.

Calculating inter-rater agreement is not as difficult as it may seem. Here are the steps to follow:

Step 1: Choose a measure of agreement

There are several measures of agreement that can be used, such as percentage agreement, Cohen`s kappa, and Fleiss` kappa. Each measure has its own strengths and weaknesses and the choice of measure will depend on the nature of the data being evaluated and the goals of the study.

Step 2: Select the raters

The raters who will be assessing the data should be selected based on their expertise and experience in the relevant field. It is also important to ensure that there is no bias or conflict of interest among the raters.

Step 3: Define the categories or scoring criteria

The categories or scoring criteria that will be used to evaluate the data should be clearly defined. This will help to ensure that the raters are assessing the data consistently and accurately.

Step 4: Assign the ratings

The raters should be given the data to evaluate independently and they should assign the ratings based on the defined categories or scoring criteria.

Step 5: Calculate the inter-rater agreement

Once the ratings have been assigned, the inter-rater agreement can be calculated using the chosen measure of agreement. For example, if Cohen`s kappa was chosen as the measure of agreement, the formula for calculating kappa would be:

k = (P(A) – P(E)) / (1 – P(E))


P(A) = observed proportion of agreement

P(E) = expected proportion of agreement by chance

Step 6: Interpret the results

The results of the inter-rater agreement calculation should be interpreted based on the specific measure of agreement used. Generally, values closer to 1 indicate higher agreement, while values closer to 0 indicate lower agreement.

In summary, calculating inter-rater agreement is an important tool for ensuring the reliability and consistency of data evaluation. By following these simple steps, researchers and quality controllers can ensure that their results are accurate and reliable.