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p2: a random effects model with covariates for directed graphs

Author

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  • Marijtje A. J. van Duijn
  • Tom A. B. Snijders
  • Bonne J. H. Zijlstra

Abstract

A random effects model is proposed for the analysis of binary dyadic data that represent a social network or directed graph, using nodal and/or dyadic attributes as covariates. The network structure is reflected by modeling the dependence between the relations to and from the same actor or node. Parameter estimates are proposed that are based on an iterated generalized least‐squares procedure. An application is presented to a data set on friendship relations between American lawyers.

Suggested Citation

  • Marijtje A. J. van Duijn & Tom A. B. Snijders & Bonne J. H. Zijlstra, 2004. "p2: a random effects model with covariates for directed graphs," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(2), pages 234-254, May.
    • Handle: RePEc:bla:stanee:v:58:y:2004:i:2:p:234-254
    DOI: 10.1046/j.0039-0402.2003.00258.x
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    Cited by:

    1. Bryan S. Graham, 2014. "An econometric model of link formation with degree heterogeneity," NBER Working Papers 20341, National Bureau of Economic Research, Inc.
    2. Bryan S. Graham, 2015. "An econometric model of link formation with degree heterogeneity," CeMMAP working papers 43/15, Institute for Fiscal Studies.
    3. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.

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