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Bradley-Terry Models in R

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  • Firth, David

Abstract

This paper describes the R add-on package BradleyTerry, which facilitates the specification and fitting of Bradley-Terry logit models to pair-comparison data. Included are the standard "unstructured" Bradley-Terry model, structured versions in which the parameters are related through a linear predictor to explanatory variables, and the possibility of an order or "home advantage" effect. Model fitting is either by maximum likelihood or by bias-reduced maximum likelihood in which the first-order asymptotic bias of parameter estimates is eliminated. Also provided are a simple and efficient approach to handling missing covariate data, and suitably-defined residuals for diagnostic checking of the linear predictor; these are new methodological contributions which will be discussed in greater detail elsewhere.

Suggested Citation

  • Firth, David, 2005. "Bradley-Terry Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i01).
    • Handle: RePEc:jss:jstsof:v:012:i01
    DOI: http://hdl.handle.net/10.18637/jss.v012.i01
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    References listed on IDEAS

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    1. Douglas Critchlow & Michael Fligner, 1991. "Paired comparison, triple comparison, and ranking experiments as generalized linear models, and their implementation on GLIM," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 517-533, September.
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    Cited by:

    1. Yee, Thomas W., 2010. "The VGAM Package for Categorical Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i10).
    2. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630, April.
    3. Anna Gottard & Giorgio Calzolari, 2014. "Alternative estimating procedures for multiple membership logit models with mixed effects: indirect inference and data cloning," Econometrics Working Papers Archive 2014_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Wickelmaier, Florian & Strobl, Carolin & Zeileis, Achim, 2012. "Psychoco: Psychometric Computing in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i01).
    5. repec:jss:jstsof:32:i10 is not listed on IDEAS
    6. David G. Hamilton & Martin J. Whiting & Sarah R. Pryke, 2013. "Fiery frills: carotenoid-based coloration predicts contest success in frillneck lizards," Behavioral Ecology, International Society for Behavioral Ecology, vol. 24(5), pages 1138-1149.
    7. Turner, Heather & Firth, David, 2012. "Bradley-Terry Models in R: The BradleyTerry2 Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i09).
    8. Vicente Rodríguez Montequín & Joaquín Manuel Villanueva Balsera & Marina Díaz Piloñeta & César Álvarez Pérez, 2020. "A Bradley-Terry Model-Based Approach to Prioritize the Balance Scorecard Driving Factors: The Case Study of a Financial Software Factory," Mathematics, MDPI, vol. 8(2), pages 1-15, February.
    9. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630.

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