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Advances in GLIM and Statistical Modelling pp 125–130Cite as

A class of models for the simultaneous analysis of square contingency tables

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

Abstract

A class of models is presented for the analysis of square contingency tables. The models fall in the class of loglinear models or models with logbilinear terms for the association. The models in this class differ in three ways: 1. the association is either assumed to be symmetric or asymmetric 2. the association is assumed to be completely different in each subtable, to have the same form but having different strength, or to be the same and having the same strength 3. for each subtable separately the association that is proposed is full, or has a logbilinear form, or is uniform. An example from research on social mobility will be discussed. The stability of the parameter estimates is studied with the jackknife.

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Author information

Authors and Affiliations

  1. Department of Sociology, University of Utrecht, Postbus 80.140, 3508 TC, Utrecht, The Netherlands

    Peter G. M. van der Heijden & Wim Jansen

Authors
  1. Peter G. M. van der Heijden
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  2. Wim Jansen
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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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van der Heijden, P.G.M., Jansen, W. (1992). A class of models for the simultaneous analysis of square contingency tables. 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_20

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  • DOI: https://doi.org/10.1007/978-1-4612-2952-0_20

  • 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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