188 Handbook of Big Data
P. Erdos and A. Renyi. On random graphs I. Publicationes Mathematicae Debrecen,6:
290–297, 1959.
L. Euler. Solutio problematis ad geometriam situs pertinentis. Commentarii Academiae
Scientiarum Petropolitanae, 8:128–140, 1741.
R.A. Fisher. On the mathematical foundations of theoretical statistics. In Philosophical
Transactions of the Royal Society of London. Series A, Containing Papers of a Mathe-
matical or Physical Character, pp. 309–368, 1922.
B.K. Fosdick and P.D. Hoff. Testing and modeling dependencies between a network and
nodal attributes. arXiv preprint arXiv:1306.4708, 2013.
J.H. Fowler and N.A. Christakis. Estimating peer effects on health in social networks: A
response to Cohen-Cole and Fletcher; Trogdon, Nonnemaker, Pais. Journal of Health
Economics, 27(5):1400, 2008.
E.N. Gilbert. Random graphs. The Annals of Mathematical Statistics, 30:1141–1144, 1959.
A. Goldenberg, A.X. Zheng, S.E. Fienberg, and E.M. Airoldi. A survey of statistical network
models. Foundations and Trends
in Machine Learning, 2(2):129–233, 2010.
S. Greenland. An introduction to instrumental variables for epidemiologists. International
Journal of Epidemiology, 29(4):722–729, 2000.
M.E. Halloran and C.J. Struchiner. Causal inference in infectious diseases. Epidemiology,6
(2):142–151, 1995.
M.A. Hernan. A definition of causal effect for epidemiological research. Journal of
Epidemiology and Community Health, 58(4):265–271, 2004.
P. Hoff, B. Fosdick, A. Volfovsky, and K. Stovel. Likelihoods for fixed rank nomination
networks. Network Science, 1(03):253–277, 2013.
P.D. Hoff. Bilinear mixed-effects models for dyadic data. Journal of the American Statistical
Association, 100(469):286–295, 2005.
P.D. Hoff. Discussion of “Model-based clustering for social networks,” by Handcock, Raftery
and Tantrum. Journal of the Royal Statistical Society, Series A, 170(2):339, 2007.
P.D. Hoff. Modeling homophily and stochastic equivalence in symmetric relational data. In
J.C. Platt, D. Koller, Y. Singer, and S. Roweis (eds.), Advances in Neural Information
Processing Systems 20, pp. 657–664. MIT Press, Cambridge, MA, 2008. http://cran.r-
project.org/web/packages/eigenmodel/.
P.D. Hoff, A.E. Raftery, and M.S. Handcock. Latent space approaches to social network
analysis. Journal of the American Statistical Association, 97(460):1090–1098, 2002.
P.W. Holland, K.B. Laskey, and S. Leinhardt. Stochastic blockmodels: First steps. Social
Networks, 5(2):109–137, 1983.
B. Karrer and M.E.J. Newman. Stochastic blockmodels and community structure in
networks. Physical Review E, 83(1):016107, 2011.
E.D. Kolaczyk. Statistical Analysis of Network Data. Springer, New York, 2009.
E.D. Kolaczyk and P.N. Krivitsky. On the question of effective sample size in network
modeling. arXiv preprint arXiv:1112.0840, 2011.