Airoldi, E. M., Blei, D. M., Fienberg, S. E., & Xing, E. P. (2008). Mixed membership stochastic blockmodels. Journal of Machine Learning Research, 9, 1981–2014.
Breiger, R. L., Boorman, S. A., & Arabie, P. (1975). An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling. Journal of Mathematical Psychology, 12
(3), 328–383.
Currarini, S., Jackson, M. O., & Pin, P. (2010). Identifying the roles of race-based choice and chance in high school friendship network formation. Proceedings of the National Academy of Sciences, 107
(11), 4857–4861.
Fletcher, J. M., & Ross, S. L. (2012). Estimating the effects of friendship networks on health behaviors of adolescents. Technical report, National Bureau of Economic Research, Cambridge, MA.
Frank, O., & Strauss, D. (1986). Markov graphs. Journal of the American Statistical Association, 81
(395), 832–842. ISSN .
Geweke, J. (1991). Efficient simulation from the multivariate normal and student-t distributions subject to linear constraints and the evaluation of constraint probabilities. In Computing Science and Statistics: Proceedings of the 23rd symposium on the interface, pp. 571–578.
Gill, P. S., & Swartz, T. B. (2001). Statistical analyses for round robin interaction data. Canadian Journal of Statistics, 29
(2), 321–331. ISSN .
Goodreau, S. M., Kitts, J. A., & Morris, M. (2009). Birds of a feather, or friend of a friend? using exponential random graph models to investigate adolescent social networks.* Demography, 46
(1), 103–125.
Handcock, M. S., & Gile, K. J. (2010). Modeling social networks from sampled data. Annals of Applied Statistics, 4
(1), 5–25. ISSN . 10.1214/08-AOAS221 Retrieved from http://dx.doi.org/10.1214/08-AOAS221.
Harris, K. M., Halpern, C. T., Whitsel, E., Hussey, J., Tabor, J., Entzel, P., & Udry, J. R. (2009). The national longitudinal study of adolescent health: Research design. Retrieved from http://www.cpc.unc.edu/projects/addhealth/design (December 15, 2012).
Hoff, P. D. (2005). Bilinear mixed-effects models for dyadic data. Journal of the American Statistical Association, 100
(469), 286–295. ISSN .
Hoff, P. D. (2007). Extending the rank likelihood for semiparametric copula estimation. Annals of Applied Statistics, 1
(1), 265–283. ISSN .
Hoff, P. D. (2009a). Multiplicative latent factor models for description and prediction of social networks. Computational and Mathematical Organization Theory, 15
(4), 261–272.
Hoff, P. D. (2009b). A first course in bayesian statistical methods. Springer Texts in Statistics. New York, NY: Springer. ix, 270 p. EUR 64.15; SFR 99.50.
Hoff, P. D., Raftery, A. E., & Handcock, M. S. (2002). Latent space approaches to social network analysis. Journal of the American Statistical Association, 97
(460), 1090–1098. ISSN .
Holland, P. W., & Leinhardt, S. (1981). An exponential family of probability distributions for directed graphs. Journal of the American Statistical Association, 76
(373), 33–50.
Kiuru, N., Burk, W. J., Laursen, B., Salmela-Aro, K., & Nurmi, J. E. (2010). Pressure to drink but not to smoke: Disentangling selection and socialization in adolescent peer networks and peer groups. Journal of Adolescence, 33
(6), 801–812.
Krivitsky, P. N., & Butts, C. T. (2012). Exponential-family random graph models for rank-order relational data. Retrieved from http://arxiv.org/abs/1210.0493 (December 15, 2012).
Li, H., & Loken, E. (2002). A unified theory of statistical analysis and inference for variance component models for dyadic data. Statistics Sinica, 12
(2), 519–535. ISSN .
Macdonald-Wallis, K., Jago, R., Page, A. S., Brockman, R., & Thompson, J. L. (2011). School-based friendship networks and children's physical activity: A spatial analytical approach. Social Science & Medicine, 73
(1), 6–12.
Moody, J., Brynildsen, W. D., Osgood, D. W., Feinberg, M. E., & Gest, S. (2011). Popularity trajectories and substance use in early adolescence. Social Networks, 33
(2), 101–112.
Moreno, J. L. (1953). Who shall survive? Foundations of sociometry, group psychotherapy and socio-drama.
Mustang, OK: Beacon House.
Moreno, J. L. (1960). The sociometry reader.
New York, NY: Free Press.
Nowicki, K., & Snijders, T. A. B. (2001). Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association, 96
(455), 1077–1087. ISSN .
Pettitt, A. N. (1982). Inference for the linear model using a likelihood based on ranks. Journal of the Royal Statistical Society B, 44
(2), 234–243. ISSN .
Rodriguez-Yam, G., Davis, R. A., & Scharf, L. L. (2004). Efficient Gibbs sampling of truncated multivariate normal with application to constrained linear regression. Unpublished manuscript.
Sampson, S. F. (1969). Crisis in a cloister. Unpublished doctoral dissertation, Cornell University, Ithaca, NY.
Severini, T. A. (1991). On the relationship between Bayesian and non-Bayesian interval estimates. Journal of the Royal Statistical Society B, 53
(3), 611–618. ISSN .
Snijders, T. A. B., Pattison, P. E., Robins, G. L., & Handcock, M. S. (2006). New specifications for exponential random graph models. Sociological Methodology, 36
(1), 99–153.
Thomas, S. L. (2000). Ties that bind: A social network approach to understanding student integration and persistence. Journal of Higher Education, 71, 591–615.
van Duijn, Marijtje A. J., Snijders, Tom A. B., & Zijlstra, Bonne J. H. (2004).
p
2: A random effects model with covariates for directed graphs. Statistica Neerlandica, 58
(2), 234–254. ISSN .
Warner, R., Kenny, D. A., & Stoto, M. (1979). A new round robin analysis of variance for social interaction data. Journal of Personality and Social Psychology, 37, 1742–1757.
Wasserman, S., & Pattison, P. (1996). Logit models and logistic regressions for social networks: I. an introduction to markov graphs andp. Psychometrika, 61
(3), 401–425.
Weerman, F. M. (2011). Delinquent peers in context: A longitudinal network analysis of selection and influence effects. Criminology, 49
(1), 253–286.
Weerman, F. M., & Smeenk, W. H. (2005). Peer similarity in delinquency for different types of friends: A comparison using two measurement methods. Criminology, 43
(2), 499–524.
Wong, G. Y. (1982). Round robin analysis of variance via maximum likelihood. Journal of the American Statistical Association, 77
(380), 714–724. ISSN .
