title: A vector space method to quantify agreement in qualitative data.
abstract: Interrater agreement in qualitative research is rarely quantified. We present a new method for assessing interrater agreement in the coding of focus group transcripts, based on vector space methods. We also demonstrate similarities between this vector method and two previously published interrater agreement methods. Using these methods, we showed that interrater agreement for the qualitative data was quite low, attributable in part to the subjective nature of the codes and in part to the very large number of possible codes. These methods of assessing interrater agreement have the potential to be useful in determining and improving reliability of qualitative codings.
authors.affiliation: Departments of Biomedical Informatics (DJM, JSA, RK) and Sociomedical Sciences (RK)Columbia University, New York, NY, USA.
authors.forename: Delano J
authors.initials: DJ
authors.lastname: McFarlane
authors.forename: Jessica S
authors.initials: JS
authors.lastname: Ancker
authors.forename: Rita
authors.initials: R
authors.lastname: Kukafka
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003299:Cooperative Behavior; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D009626:Terminology as Topic; D014481:United States