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The class of CUB models: statistical foundations, inferential issues and empirical evidence

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  • Alan Agresti

    (University of Florida)

  • Maria Kateri

    (RWTH Aachen University)

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  • Alan Agresti & Maria Kateri, 2019. "The class of CUB models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 445-449, September.
    • Handle: RePEc:spr:stmapp:v:28:y:2019:i:3:d:10.1007_s10260-019-00468-8
    DOI: 10.1007/s10260-019-00468-8
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    References listed on IDEAS

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    1. Anestis Touloumis & Alan Agresti & Maria Kateri, 2013. "GEE for Multinomial Responses Using a Local Odds Ratios Parameterization," Biometrics, The International Biometric Society, vol. 69(3), pages 633-640, September.
    2. Gerhard Tutz & Micha Schneider & Maria Iannario & Domenico Piccolo, 2017. "Mixture models for ordinal responses to account for uncertainty of choice," 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. 11(2), pages 281-305, June.
    3. Alan Agresti & Maria Kateri, 2017. "Ordinal probability effect measures for group comparisons in multinomial cumulative link models," Biometrics, The International Biometric Society, vol. 73(1), pages 214-219, March.
    4. Alan Agresti & Claudia Tarantola, 2018. "Simple ways to interpret effects in modeling ordinal categorical data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 210-223, August.
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    Cited by:

    1. Alessandro Barbiero, 2021. "Inducing a desired value of correlation between two point-scale variables: a two-step procedure using copulas," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(2), pages 307-334, June.

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