Bangdiwala's B

{{Short description|Measure of inter-rater agreement}}

Bangdiwala's B statistic was created by Shrikant Bangdiwala in 1985 and is a measure of inter-rater agreement.Bangwidala S (1985) A graphical test for observer agreement. Proc 45th Int Stats Institute Meeting, Amsterdam, 1, 307–308Bangdiwala K (1987) Using SAS software graphical procedures for the observer agreement chart. Proc SAS User's Group International Conference, 12, 1083-1088 While not as commonly used as the kappa statistic the B test has been used by various workers.Grill E, Mansmann U, Cieza A, Stucki G (2007) Assessing observer agreement when describing and classifying functioning with the International Classification of Functioning, Disability and Health. J Rehabil Med 39(1):71-76Ossa XM, Munoz S, Amigo H, Bangdiwala SI (2010) Secular trend in age at menarche in indigenous and nonindigenous women in Chile. Am J Hum Biol 22(5):688-694Jenkins V, Solis-Trapala I, Langridge C, Catt S, Talbot DC, Fallowfield LJ (2011) What oncologists believe they said and what patients believe they heard: an analysis of phase I trial discussions. J Clin Oncol 29(1):61-68 {{doi|10.1200/JCO.2010.30.0814}}Bangdiwala SI, Haedo, AS, Natal, ML, Villaveces A (2008) The Agreement Chart as an Alternative to the Receiver-Operating Characteristic Curve for Diagnostic Tests. J Clin Epidemiol 61, 866–874 While it is principally used as a graphical aid to inter observer agreement, its asymptotic distribution is known.

Definition

The test is applicable to testing the agreement between two observers. It is defined to be

B = \frac{ \sum_{i=1}^k n_{ ii }^2 }{ \sum_{i=1}^k n_{ i. } n_{ .i } }

where n_{ii} are the values on the main diagonal,

n_{i.} is the ith row total, and

n_{.i} is the ith column total of the contingency table.

The value of B varies in value between 0 (no agreement) and +1 (perfect agreement).

In large samples B has a normal distribution whose variance has a complicated expression.Bangdiwala, Shrikant I. (1988) [http://www.stat.ncsu.edu/information/library/mimeo.archive/ISMS_1988_1859.pdf "The Agreement Chart"]. Department of Biostatistics, University of North Carolina at Chapel Hill, Institute of Statistics Mimeo Series No. 1859 (Appendix) For small samples a permutation test is indicated.

Guidance on its use and its extension to n x n tables have been provided by Munoz & Bangdiwala.Munoz SR & Bangdiwala SI (1997) Interpretation of Kappa and B statistics measures of agreement. J Applied Stats 24 (1) 105-112 {{doi|10.1080/02664769723918}} It may be more useful than the more commonly used Cohen's kappa in some circumstances.Shankara V & Bangdiwala SI (2008) "Behavior of agreement measures in the presence of zero cells and biased marginal distributions". Journal of Applied Statistics, 35 (4), 445-464 {{doi|10.1080/02664760701835052}}

Tutorials and examples

Worked examples of the use of Bangdiwala's B have been published.Friendly, M (1995) [http://www.datavis.ca/courses/grcat/grc3.html#H2_62:Bangdiwala's "Bangdiwala's Observer Agreement Chart"] Webpage: Categorical Data Analysis with Graphics (Part 3: Plots for two-way frequency tables) http://www.datavis.ca/courses/grcat/grc3.html#H2_62:Bangdiwala'sStokes, M. (2011) [http://support.sas.com/resources/papers/proceedings11/346-2011.pdf "Up To Speed With Categorical Data Analysis"]. SAS Global Forum 2011, Paper 346-2011

The statistical programming language R has a set of functions that will compute the B test,[http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/vcd/html/00Index.html "Documentation for package ‘vcd’ version 1.2-13"] {{Webarchive|url=https://web.archive.org/web/20130810183452/http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/vcd/html/00Index.html |date=2013-08-10 }}, R package: Visualizing Categorical Data and a tutorial on the use of a test using these R functions is available.Friendly, M.

[https://cran.r-project.org/web/packages/vcdExtra/vignettes/vcd-tutorial.pdf "Working with categorical data with R and the vcd and vcdExtra packages"], CRAN R project website.

See also

References