Probability Models and Statistical Analyses for Ranking Data

  • Michael A. Fligner
  • Joseph S. Verducci

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

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Ranking Models with Item Covariates

    1. Douglas E. Critchlow, Michael A. Fligner
      Pages 1-19
  3. Nonparametric Methods of Ranking from Paired Comparisons

    1. H. A. David, D. M. Andrews
      Pages 20-36
  4. On the Babington Smith Class of Models for Rankings

    1. Harry Joe, Joseph S. Verducci
      Pages 37-52
  5. Latent Structure Models for Ranking Data

    1. M. A. Croon, R. Luijkx
      Pages 53-74
  6. Modelling and Analysing Paired Ranking Data

    1. Paul D. Feigin
      Pages 75-91
  7. Maximum Likelihood Estimation in Mallows’s Model Using Partially Ranked Data

  8. Extensions of Mallows’ ϕ Model

    1. Lyinn Chung, John I. Marden
      Pages 108-139
  9. Rank Correlations and the Analysis of Rank-Based Experimental Designs

  10. Applications of Thurstonian Models to Ranking Data

  11. Probability Models on Rankings and the Electoral Process

  12. Permutations and Regression Models

    1. Peter McCullagh
      Pages 196-215
  13. Aggregation Theorems and the Combination of Probabilistic Rank Orders

  14. A Nonparametric Distance Model for Unidimensional Unfolding

    1. Rian van Blokland-Vogelesang
      Pages 241-276
  15. Miscellanea

    1. Front Matter
      Pages 277-277
    2. Peter McCullagh
      Pages 278-283
    3. G. L. Thompson
      Pages 294-298
    4. Peter McCullagh, Jianming Ye
      Pages 299-306

About these proceedings

Introduction

In June of 1990, a conference was held on Probablity Models and Statisti­ cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians. The conference took place at the University of Massachusetts, Amherst, and was attended by 36 participants, including statisticians, mathematicians, psychologists and sociologists from the United States, Canada, Israel, Italy, and The Nether­ lands. There were 18 presentations on a wide variety of topics involving ranking data. This volume is a collection of 14 of these presentations, as well as 5 miscellaneous papers that were contributed by conference participants. We would like to thank Carole Kohanski, summer program coordinator for the American Mathematical Society, for her assistance in arranging the conference; M. Steigerwald for preparing the manuscripts for publication; Martin Gilchrist at Springer-Verlag for editorial advice; and Persi Diaconis for contributing the Foreword. Special thanks go to the anonymous referees for their careful readings and constructive comments. Finally, we thank the National Science Foundation for their sponsorship of the AMS-IMS-SIAM Joint Summer Programs. Contents Preface vii Conference Participants xiii Foreword xvii 1 Ranking Models with Item Covariates 1 D. E. Critchlow and M. A. Fligner 1. 1 Introduction. . . . . . . . . . . . . . . 1 1. 2 Basic Ranking Models and Their Parameters 2 1. 3 Ranking Models with Covariates 8 1. 4 Estimation 9 1. 5 Example. 11 1. 6 Discussion. 14 1. 7 Appendix . 15 1. 8 References.

Keywords

ANOVA Likelihood Random variable correlation data analysis expectation–maximization algorithm matching permutations ranking data

Editors and affiliations

  • Michael A. Fligner
    • 1
  • Joseph S. Verducci
    • 1
  1. 1.Department of StatisticsThe Ohio State UniversityColumbusUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-2738-0
  • Copyright Information Springer-Verlag New York 1993
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-97920-5
  • Online ISBN 978-1-4612-2738-0
  • Series Print ISSN 0930-0325
  • About this book