A vector space method to quantify agreement in qualitative data. Academic Article uri icon

Overview

MeSH

  • Algorithms
  • Artificial Intelligence
  • United States

MeSH Major

  • Cooperative Behavior
  • Information Storage and Retrieval
  • Natural Language Processing
  • Pattern Recognition, Automated
  • Terminology as Topic

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.

publication date

  • November 6, 2008

has subject area

  • Algorithms
  • Artificial Intelligence
  • Cooperative Behavior
  • Information Storage and Retrieval
  • Natural Language Processing
  • Pattern Recognition, Automated
  • Terminology as Topic
  • United States

Research

keywords

  • Journal Article

Identity

Language

  • eng

PubMed Central ID

  • PMC2655941

PubMed ID

  • 18999026

Additional Document Info

start page

  • 455

end page

  • 459