![]() IRR is important to know since you don’t want to report inconsistently coded data, which would skew your project’s results. IRR is the set of metrics (Kappa score and % Agreement) you can look at to indicate how similar or dissimilar your data is being coded across all researchers. This is where inter-rater reliability (IRR) comes in. Say you have 3 researchers coding 20 different interviews for a qualitative project but as the project manager, you want to know whether the coding patterns between all 3 researchers are consistent and unified before you report the results. Reason 1: Inter-rater reliability (IRR) tells us how similar or dissimilar we are coding our data. ![]() After all, the goal of qualitative research is to find out how people think or feel about a certain topic, which isn’t always easy to categorize! Coding qualitative data into both narrow and broad themes, is the best way to classify non-numerical participant responses. Most people who do qualitative research, which analyzes non-numerical information, such as interviews, open-ended questionnaires, and observations, know that it includes a LOT of coding. 4 Reasons to Celebrate Inter-rater reliability (IRR) in Qualitative Research ![]()
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