title: The agreement chart.
abstract: 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.
authors.affiliation: Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. kant@unc.edu
authors.forename: Shrikant I
authors.initials: SI
authors.lastname: Bangdiwala
authors.forename: Viswanathan
authors.initials: V
authors.lastname: Shankar
mesh_terms: D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D015588:Observer Variation; D015203:Reproducibility of Results
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