Ranking Items Scalably with the Bradley-Terry Model

Introducing the BradleyTerryScalable package

Ella Kaye true

slides materials package


I am very excited to be introducing the package BradleyTerryScalable at useR!2017. The package is available on GitHub.

BradleyTerryScalable is an R package for fitting the Bradley-Terry model to pair-comparison data, to enable statistically principled ranking of a potentially large number of objects.

Given a number of items for which we have pair-comparison data, the Bradley-Terry model assigns a ‘strength’ parameter to each item. These can be used to rank the items. Moreover, they can be used to determine the probability that any given item will ‘beat’ any other given item when they are compared. Further details of the mathematical model, and the algorithms used to fit it, are available in the package vignette.

Event details

Event: useR!2017

Date: July 6th, 2017

Time: 11:36 AM

Location: Brussels, Belgium


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Text and figures are licensed under Creative Commons Attribution CC BY-SA 4.0. Source code is available at https://github.com/EllaKaye/ellakaye-distill, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".


For attribution, please cite this work as

Kaye (2017, July 6). ELLA KAYE: Ranking Items Scalably with the Bradley-Terry Model. Retrieved from https://ellakaye.rbind.io/talks/2017-07-06-introducing-bradleyterryscalable/

BibTeX citation

  author = {Kaye, Ella},
  title = {ELLA KAYE: Ranking Items Scalably with the Bradley-Terry Model},
  url = {https://ellakaye.rbind.io/talks/2017-07-06-introducing-bradleyterryscalable/},
  year = {2017}