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Marginal modelling of Correlated Ordinal Data using an n-way Plackett Distribution

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Advances in GLIM and Statistical Modelling

Part of the book series: Lecture Notes in Statistics ((LNS,volume 78))

Abstract

Popular approaches to model the marginal probabilities of a multivariate categorical response vector are the empirical least squares method (implemented in the SAS procedure CATMOD [15]) and the generalized estimating equations method (Liang and Zeger [7]). Neither of the two is a likelihood method.

* Author supported by an NFWO grant.

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References

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Author information

Authors and Affiliations

  1. Department of Epidemiology, Biostatistical Centre, Capucijnenvoer 35, B3000, Leuven, Belgium

    Emmanuel Lesaffre

Authors
  1. Geert Molenberghs
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  2. Emmanuel Lesaffre
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Editor information

Editors and Affiliations

  1. Seminar für Statistik, University of Munich, D-8000, Munich 22, Germany

    Ludwig Fahrmeir

  2. Centre for Applied Statistics, Lancaster University, Fylde College, Lancaster, LA1 4YF, UK

    Brian Francis

  3. Faculty of Science, Computing and Engineering, Polytechnic of North London, London, N7 8DB, England

    Robert Gilchrist

  4. Institut für Statistik, University of Regensburg, Germany

    Gerhard Tutz

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© 1992 Springer-Verlag New York, Inc.

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Molenberghs, G., Lesaffre, E. (1992). Marginal modelling of Correlated Ordinal Data using an n-way Plackett Distribution. In: Fahrmeir, L., Francis, B., Gilchrist, R., Tutz, G. (eds) Advances in GLIM and Statistical Modelling. Lecture Notes in Statistics, vol 78. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2952-0_22

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  • DOI: https://doi.org/10.1007/978-1-4612-2952-0_22

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97873-4

  • Online ISBN: 978-1-4612-2952-0

  • eBook Packages: Springer Book Archive

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