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Analysing partial ranks by using smoothed paired comparison methods: an investigation of value orientation in Europe

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  • Brian Francis
  • Regina Dittrich
  • Reinhold Hatzinger
  • Roger Penn

Abstract

Summary. This paper introduces the paired comparison model as a suitable approach for the analysis of partially ranked data. For example, the Inglehart index, collected in international social surveys to examine shifts in post‐materialistic values, generates such data on a set of attitude items. However, current analysis methods have failed to account for the complex shifts in individual item values, or to incorporate subject covariates. The paired comparison model is thus developed to allow for covariate subject effects at the individual level, and a reparameterization allows the inclusion of smooth non‐linear effects of continuous covariates. The Inglehart index collected in the 1993 International Social Science Programme survey is analysed, and complex non‐linear changes of item values with age, level of education and religion are identified. The model proposed provides a powerful tool for social scientists.

Suggested Citation

  • Brian Francis & Regina Dittrich & Reinhold Hatzinger & Roger Penn, 2002. "Analysing partial ranks by using smoothed paired comparison methods: an investigation of value orientation in Europe," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(3), pages 319-336, July.
    • Handle: RePEc:bla:jorssc:v:51:y:2002:i:3:p:319-336
    DOI: 10.1111/1467-9876.00271
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    Cited by:

    1. Gunther Schauberger & Andreas Groll & Gerhard Tutz, 2018. "Analysis of the importance of on-field covariates in the German Bundesliga," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(9), pages 1561-1578, July.
    2. Yu-Shan Shih & Kuang-Hsun Liu, 2019. "Regression trees for detecting preference patterns from rank data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 683-702, September.
    3. Alexandra Grand & Regina Dittrich & Brian Francis, 2015. "Markov models of dependence in longitudinal paired comparisons: an application to course design," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(2), pages 237-257, April.
    4. Jianbo Li & Minggao Gu & Tao Hu, 2012. "General partially linear varying-coefficient transformation models for ranking data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1475-1488, January.
    5. Antonio D’Ambrosio & Willem J. Heiser, 2016. "A Recursive Partitioning Method for the Prediction of Preference Rankings Based Upon Kemeny Distances," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 774-794, September.
    6. Martin Kroh, 2008. "The Preadult Origins of Post-Materialism: A Longitudinal Sibling Study," SOEPpapers on Multidisciplinary Panel Data Research 101, DIW Berlin, The German Socio-Economic Panel (SOEP).
    7. Dittrich, Regina & Francis, Brian & Hatzinger, Reinhold & Katzenbeisser, Walter, 2006. "Modelling dependency in multivariate paired comparisons: A log-linear approach," Mathematical Social Sciences, Elsevier, vol. 52(2), pages 197-209, September.
    8. Martin Kroh, 2008. "The Preadult Origins of Post-Materialism: A Longitudinal Sibling Study," Discussion Papers of DIW Berlin 797, DIW Berlin, German Institute for Economic Research.

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