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The Rasch Model, Some Extensions and their Relation to the Class of Generalized Linear Models

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Statistical Modelling

Part of the book series: Lecture Notes in Statistics ((LNS,volume 57))

Summary

Assumptions and different methods of estimation of the Rasch model (RM) are presented as well as its formulation as a quasi-loglinear model. Expressing the RM in the context of GLMs allows a unitary treatment of goodness-of-fit tests. Two of the many extensions of the RM, the linear logistic test model and the linear logistic test model with relaxed assumptions are presented. Examples how these models can be fitted using GLIM are provided.

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Author information

Authors and Affiliations

  1. Psychiatrische Universitätsklinik, Vienna, Austria

    Reinhold Hatzinger

Authors
  1. Reinhold Hatzinger
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Editor information

Editors and Affiliations

  1. Istituto di Biometria e Statistica Medica, Via Venezian, 1, 20133, Milano, Italy

    Adriano Decarli

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

    Brian J. Francis

  3. Polytechnic of North London, Holloway Road, N7 8DB, London, UK

    Robert Gilchrist

  4. Insitut für Statistik, Universität Innsbruck, Innrain 52, 6020, Innsbruck, Austria

    Gilg U. H. Seeber

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© 1989 Springer-Verlag Berlin Heidelberg

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Hatzinger, R. (1989). The Rasch Model, Some Extensions and their Relation to the Class of Generalized Linear Models. In: Decarli, A., Francis, B.J., Gilchrist, R., Seeber, G.U.H. (eds) Statistical Modelling. Lecture Notes in Statistics, vol 57. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3680-1_20

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  • DOI: https://doi.org/10.1007/978-1-4612-3680-1_20

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97097-4

  • Online ISBN: 978-1-4612-3680-1

  • eBook Packages: Springer Book Archive

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