Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp
 Stanley Wasserman,
 Philippa Pattison
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Spanning nearly sixty years of research, statistical network analysis has passed through (at least) two generations of researchers and models. Beginning in the late 1930's, the first generation of research dealt with the distribution of various network statistics, under a variety of null models. The second generation, beginning in the 1970's and continuing into the 1980's, concerned models, usually for probabilities of relational ties among very small subsets of actors, in which various simple substantive tendencies were parameterized. Much of this research, most of which utilized log linear models, first appeared in applied statistics publications.
But recent developments in social network analysis promise to bring us into a third generation. The Markov random graphs of Frank and Strauss (1986) and especially the estimation strategy for these models developed by Strauss and Ikeda (1990; described in brief in Strauss, 1992), are very recent and promising contributions to this field. Here we describe a large class of models that can be used to investigate structure in social networks. These models include several generalizations of stochastic blockmodels, as well as models parameterizing global tendencies towards clustering and centralization, and individual differences in such tendencies. Approximate model fits are obtained using Strauss and Ikeda's (1990) estimation strategy.
In this paper we describe and extend these models and demonstrate how they can be used to address a variety of substantive questions about structure in social networks.
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 Title
 Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp
 Journal

Psychometrika
Volume 61, Issue 3 , pp 401425
 Cover Date
 19960901
 DOI
 10.1007/BF02294547
 Print ISSN
 00333123
 Online ISSN
 18600980
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 categorical data analysis
 social network analysis
 random graphs
 Industry Sectors
 Authors

 Stanley Wasserman ^{(1)}
 Philippa Pattison ^{(2)}
 Author Affiliations

 1. University of Illinois, 603 East Daniel Street, 61820, Champaign, IL
 2. University of Melbourne, USA