![]() ![]() 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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