The agreement chart

Shrikant I. Bangdiwala, Viswanathan Shankar

Research output: Contribution to journalArticlepeer-review

56 Scopus citations


Background: When assessing the concordance between two methods of measurement of ordinal categorical data, summary measures such as Cohen's (1960) kappa or Bangdiwala's (1985) B-statistic are used. However, a picture conveys more information than a single summary measure. Methods. We describe how to construct and interpret Bangdiwala's (1985) agreement chart and illustrate its use in visually assessing concordance in several example clinical applications. Results: The agreement charts provide a visual impression that no summary statistic can convey, and summary statistics reduce the information to a single characteristic of the data. However, the visual impression is personal and subjective, and not usually reproducible from one reader to another. Conclusions: The agreement chart should be used to complement the summary kappa or B-statistics, not to replace them. The graphs can be very helpful to researchers as an early step to understand relationships in their data when assessing concordance.

Original languageEnglish (US)
Article number97
JournalBMC Medical Research Methodology
Issue number1
StatePublished - 2013


  • B-statistic
  • Concordance
  • Intra- and inter-observer agreement
  • Kappa statistic

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics


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