, Volume 65, Issue 3, pp 281–299 | Cite as

Bayesian analysis of order-statistics models for ranking data

  • Philip L. H. Yu


In this paper, a class of probability models for ranking data, the order-statistics models, is investigated. We extend the usual normal order-statistics model into one where the underlying random variables follow a multivariate normal distribution. Bayesian approach and the Gibbs sampling technique are used for parameter estimation. In addition, methods to assess the adequacy of model fit are introduced. Robustness of the model is studied by considering a multivariate-t distribution. The proposed method is applied to analyze the presidential election data of the American Psychological Association (APA).

Key words

data augmentation Gibbs sampling order-statistics model ranking data 


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Copyright information

© The Psychometric Society 2000

Authors and Affiliations

  • Philip L. H. Yu
    • 1
  1. 1.Department of Statistics and Actuarial ScienceThe University of Hong KongHong Kong

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