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Quantitative Risk Assessment for Clustered Binary Data

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Statistical Modelling

Part of the book series: Lecture Notes in Statistics ((LNS,volume 104))

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Abstract

The effect of misspecifying the parametric response model for a univariate clustered binary outcome from a toxicological study on the assessment of dose effect and on estimating a virtually safe dose is investigated. Marginal and conditional models are contrasted.

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References

  • Cox, D. R. (1972) The analysis of multivariate binary data. Applied Statistics 21, 113–120.

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Authors
  1. Geert Molenberghs
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  2. Lieven Declerck
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  3. Marc Aerts
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Editor information

Editors and Affiliations

  1. Institut für Statistik, Universität Innsbruck, Christoph-Probst-Platz, Innsbruck, A-6020, Austria

    Gilg U. H. Seeber  & Gabriele Steckel-Berger  & 

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

    Brian J. Francis

  3. Institut für Statistik, Wirtschaftsuniversität, Augasse 2-6, Wien, A-1090, Austria

    Reinhold Hatzinger

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© 1995 Springer Science+Business Media New York

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Molenberghs, G., Declerck, L., Aerts, M. (1995). Quantitative Risk Assessment for Clustered Binary Data. In: Seeber, G.U.H., Francis, B.J., Hatzinger, R., Steckel-Berger, G. (eds) Statistical Modelling. Lecture Notes in Statistics, vol 104. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0789-4_24

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  • DOI: https://doi.org/10.1007/978-1-4612-0789-4_24

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94565-1

  • Online ISBN: 978-1-4612-0789-4

  • eBook Packages: Springer Book Archive

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