p2: a random effects model with covariates for directed graphs

p2: a random effects model with covariates for directed graphs

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. Par...

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Veröffentlicht in:Statistica Neerlandica 2004-05, Vol.58 (2), p.234-254
Hauptverfasser: van Duijn, Marijtje A. J., Snijders, Tom A. B., Zijlstra, Bonne J. H.
Format: Artikel
Sprache:eng
Schlagworte:
adjacency matrix
Attorneys
dependent binary data
GLMM
IGLS
logistic regression
p1 model
Parameter estimation
Professional relationships
random effects
social network analysis
Statistical analysis
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Zusammenfassung: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.
ISSN:0039-0402
1467-9574
DOI:10.1046/j.0039-0402.2003.00258.x