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.
- Intra- and inter-observer agreement
- Kappa statistic
ASJC Scopus subject areas
- Health Informatics