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Statistical Analysis of Multiple Sociometric Relations

1985; Volume: 80; Issue: 389 Linguagem: Inglês

10.1080/01621459.1985.10477129

1537-274X

Stephen E. Fienberg, Michael M. Meyer, Stanley Wasserman,

Mental Health Research Topics

Abstract Loglinear models are adapted for the analysis of multivariate social networks, a set of sociometric relations among a group of actors. Models that focus on the similarities and differences between the relations and models that concentrate on individual actors are discussed. This approach allows for the partitioning of the actors into blocks or subgroups. Some ideas for combining these models are described, and the various models and computational methods are applied to the analysis of data for a corporate interlock network of the 25 largest organizations in Minneapolis/St. Paul and for a classic network of 18 monks in a cloister. The computational techniques all involve variations on the standard iterative proportional-fitting algorithm used extensively in the analysis of multidimensional contingency tables. Key Words: Loglinear modelDirected graphSocial networkSociometric dataIterative proportional fittingGLIM model