Goodness of fit of social network models

Journal of the American Statistical Association

Volumn 103, Issue 481, 2008, Pages 248-258

  Hunter, David R ^a   Goodreau, Steven M ^b   Handcock, Mark S ^b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Degeneracy; Exponential random graph model; Markov chain Monte Carlo; Maximum likelihood estimation p star model

Indexed keywords

EID: 41249094522     PISSN: 01621459     EISSN: None     Source Type: Journal    
DOI: 10.1198/016214507000000446     Document Type: Article

References (23)

1. Akaike, H. (1973), "Information Theory and an Extension of the Maximum Likelihood Principle," in Second International Symposium on Information Theory, eds. B. N. Petrov and F. Csaki, Budapest: Akademiai Kaidó, pp. 267-281.
2. Besag, J. (1974), "Spatial Interaction and the Statistical Analysis of Lattice Systems," Journal of the Royal Statistical Society, Ser. B, 36, 192-225.
3. Corander, J., Dahmström, K., and Dahmström, P. (1998), "Maximum Likelihood Estimation for Markov Graphs," Research Report 1998:8, University of Stockholm, Dept. of Statistics.
4. Crouch, B., Wasserman, S., and Trachtenberg, F. (1998), "Markov Chain Monte Carlo Maximum Likelihood Estimation for p* Social Network Models," presented at the XVIII International Sunbelt Social Network Conference, Sitges, Spain.
5. Dahmström, K., and Dahmström, P. (1993), "ML Estimation of the Clustering Parameter in a Markov Graph Model," research report, University of Stockholm, Dept. of Statistics.
6. Frank, O., and Strauss, D. (1986), "Markov Graphs," Journal of the American Statistical Association, 81, 832-842.
7. Geyer, C. J., and Thompson, E. (1992), "Constrained Monte Carlo Maximum Likelihood for Dependent Data," Journal of the Royal Statistical Society, Ser. B, 54, 657-699.
8. Goodreau, S. M. (2007), "Advances in Exponential Random Graph (p*) Models Applied to a Large Social Network," Social Networks, 29, 231-248.
9. Handcock, M. S. (2002), "Statistical Models for Social Networks: Inference and Degeneracy," in Dynamic Social Network Modelling and Analysis: Workshop Summary and Papers, eds. R. Breiger, K. Carley, and P. E. Pattison, Washington, DC: National Academy Press, pp. 229-240.
10. _ (2003), "Assessing Degeneracy in Statistical Models of Social Networks," Working Paper 39, Center for Statistics and the Social Sciences, University of Washington, available at http://www.csss.washington.edu/ Papers/.
11. Holland, P. W., and Leinhardt, S. (1981), "An Exponential Family of Probability Distributions for Directed Graphs," Journal of the American Statistical Association, 76, 33-50.
12. Hunter, D. R. (2007), "Curved Exponential Family Models for Social Networks," Social Networks, 29, 216-230.
13. Hunter, D. R., and Handcock, M. S. (2006), "Inference in Curved Exponential Family Models for Networks," Journal of Computational and Graphical Statistics, 15, 565-583.
14. Lehmann, E. L. (1983), Theory of Point Estimation, New York: Wiley.
15. Morris, M. (2003), "Local Rules and Global Properties: Modeling the Emergence of Network Structure," in Dynamic Social Network Modelling and Analysis: Workshop Summary and Papers, eds. R. Breiger, K. Carley, and P. E. Pattison, Washington, DC: National Academy Press, pp. 174-186.
16. Resnick, M. D., Bearman, P. S., Blum, R. W., et al. (1997), "Protecting Adolescents From Harm: Findings From the National Longitudinal Study on Adolescent Health," Journal of the American Medical Association, 278, 823-832.
17. Schwarz, G. (1978), "Estimating the Dimension of a Model," The Annals of Statistics, 6, 461-464.
18. Snijders, T. A. B. (2002), "Markov Chain Monte Carlo Estimation of Exponential Random Graph Models," Journal of Social Structure, 3, available at www.cmu.edu/joss/content/articles/volume3/Snijders.pdf.
19. Snijders, T. A. B., Pattison, P. E., Robins, G. L., and Handcock, M. S. (2006), "New Specifications for Exponential Random Graph Models," Sociological Methodology, 36, 99-154.
20. Strauss, D., and Ikeda, M. (1990), "Pseudolikelihood Estimation for Social Networks," Journal of the American Statistical Association, 85, 204-212.
21. Udry, J. R., and Bearman, P. S. (1998), "New Methods for New Research on Adolescent Sexual Behavior," in New Perspectives on Adolescent Risk Behavior, ed. R. Jessor, New York: Cambridge University Press, pp. 241-269.
22. Wasserman, S., and Faust, K. (1994), Social Network Analysis: Methods and Applications, Cambridge, U.K.: Cambridge University Press.
23. Wasserman, S., and Pattison, P. E. (1996), "Logit Models and Logistic Regres-sion for Social Networks: I. An Introduction to Markov Graphs and p*," Psychometrika, 61, 401-425.