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Graphical Models for Dependencies and Associations

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Computational Statistics

Abstract

The role of graphical representations is described in distinguishing various special forms of independency structure that can arise with multivariate data, especially in observational studies in the social sciences. Conventions for constructing the graphs and strategies for analysing three sets of data are summarized. Finally some directions for desirable future work are outlined.

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Author information

Authors and Affiliations

  1. Psychological Institute, University of Mainz, Staudingerweg 9, 6500, Mainz, Germany

    Nanny Wermuth & D. R. Cox

  2. Nuffield College, Oxford, OX1 1NF, UK

    Nanny Wermuth & D. R. Cox

Authors
  1. Nanny Wermuth
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  2. D. R. Cox
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Editor information

Editors and Affiliations

  1. Groupe de Statistique, University of Neuchâtel, Pierre-à-Mazel 7, CH-2000, Neuchâtel, Switzerland

    Yadolah Dodge (Professor of Statistics and Operations Research) (Professor of Statistics and Operations Research)

  2. Lancaster University, GB-Lancaster, LA1 4YE, Great Britain

    Joe Whittaker (Professor of Mathematics) (Professor of Mathematics)

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© 1992 Springer-Verlag Berlin Heidelberg

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Wermuth, N., Cox, D.R. (1992). Graphical Models for Dependencies and Associations. In: Dodge, Y., Whittaker, J. (eds) Computational Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-662-26811-7_32

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  • DOI: https://doi.org/10.1007/978-3-662-26811-7_32

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-662-26813-1

  • Online ISBN: 978-3-662-26811-7

  • eBook Packages: Springer Book Archive

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