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Rank Correlations and the Analysis of Rank-Based Experimental Designs

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Probability Models and Statistical Analyses for Ranking Data

Part of the book series: Lecture Notes in Statistics ((LNS,volume 80))

Abstract

The notion of distance between two permutations is used to provide a unified treatment for various problems involving ranking data. Using the distances defined by Spearman and Kendall, the approach is illustrated in terms of the problem of concordance as well as the problem of testing for agreement among two or more populations of rankers. An extension of the notion of distance for incomplete permutations is shown to lead to a generalization of the notion of rank correlation. Applications are given to the incomplete block design as well as to the class of cyclic designs.

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Author information

Authors and Affiliations

  1. University of Ottawa, Ontario, Canada

    M. Alvo

  2. Acadia University, Nova Scotia, Canada

    P. Cabilio

Authors
  1. M. Alvo
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  2. P. Cabilio
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Editor information

Editors and Affiliations

  1. Department of Statistics, The Ohio State University, Columbus, OH, 43210, USA

    Michael A. Fligner  & Joseph S. Verducci  & 

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© 1993 Springer-Verlag New York, Inc.

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Alvo, M., Cabilio, P. (1993). Rank Correlations and the Analysis of Rank-Based Experimental Designs. In: Fligner, M.A., Verducci, J.S. (eds) Probability Models and Statistical Analyses for Ranking Data. Lecture Notes in Statistics, vol 80. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2738-0_8

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  • DOI: https://doi.org/10.1007/978-1-4612-2738-0_8

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97920-5

  • Online ISBN: 978-1-4612-2738-0

  • eBook Packages: Springer Book Archive

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