SEARCH

SEARCH BY CITATION

References

  • 1
    Christakis NA, Fowler JH. Social contagion theory: examining dynamic social networks and human behavior. Statistics in Medicine 2012. DOI: 10:1002/sim.5408.
  • 2
    Moreno JL. Who shall survive? A New Approach to the Problem of Human Interrelations, Nervous and mental disease monograph series, no. 58. Nervous and Mental Disease Publishing Co, xvi: Washington, DC, US, 1934.
  • 3
    Keating NL, Ayanian JZ, Cleary PD, Marsden PV. Factors affecting influential discussions among physicians: a social network analysis of a primary care practice. Journal of General Internal Medicine 2007; 22:794798.
  • 4
    Pham HH, O'Malley AS, Bach PB, Saiontz-Martinez C, Schrag D. Primary care physicians' links to other physicians through medicare patients: the scope of care coordination. Annals of internal medicine 2009; 150:236242.
  • 5
    Barnett ML, Christakis NA, O'Malley AJ, Onnela J-P, Keating NL, Landon BE. Physician patient-sharing networks and the cost and intensity of care in US hospitals. Medical Care 2012; 50:152160.
  • 6
    Rubin D. Bayesian inference for causal effects: the role of randomization. The Annals of Statistics 1978; 6:3458.
  • 7
    Freeman L. The Development of Social Network Analysis: A Study in the Sociology of Science. Empirical Press: Vancouver, Canada, 2004.
  • 8
    O'Malley AJ, Marsden PV. The analysis of social networks. Health Services & Outcomes Research Methodology 2008; 8(4):222269.
  • 9
    Wasserman SS, Faust K. Social Network Analysis: Methods and Applications. Cambridge University Press: Cambridge, United Kingdom, 1994.
  • 10
    Christakis NA, Fowler JH. Connected. Little, Brown and Company: New York, 2010.
  • 11
    Manski CA. Identification of endogenous social effects: the reflection problem. Review of Economic Studies 1993; 60:531542.
  • 12
    Laumann E, Marsden P, Prensky D. The boundary specification problem in network analysis. In Applied Network Analysis: A Methodological Introduction, Burt R, Minor M (eds). Sage Publication: Beverly Hills, CA, 1983; 1834.
  • 13
    Anselin L. Spatial Econometrics: Methods and Models. Kluwer Academic Publishers: Dordrecht, The Netherlands, 1988.
  • 14
    O'Malley AJ, Cotterill P, Schermerhorn ML, Landon BE. Optimal referral strategies involving treatment selection and volume-outcome relationships for aaa repair. Medical Care 2011; 49:11261132.
  • 15
    Noel H, Nyhan B. The “unfriending” problem: the consequences of homophily in friendship retention for causal estimates of social influence. Social Networks 2011; 33:211218.
  • 16
    VanderWeele TJ. Sensitivity analysis for contagion effects in social networks. Sociological Methods & Research 2011; 40(2):240255.
  • 17
    Fletcher JM. Social interactions and smoking: evidence using multiple student cohorts, instrumental variables, and school fixed effects. Health Economics 2008; 19:466484.
  • 18
    Horton NJ, Laird NM, Zahner GP. Use of multiple informant data as a predictor in psychiatric epidemiology. International Journal of Methods in Psychiatric Research 1999; 8:618.
  • 19
    VanderWeele TJ, Ogburn EL, Tchetgen Tchetgen EJ. Why and when “flawed” social network analyses still yield valid tests of no contagion. Statistics, Politics, and Policy 2012; Manuscript 1050.
  • 20
    Marsden PV, Friedkin NE. Network studies of social influence. Sociological Methods & Research 1993; 22(1):127151.
  • 21
    Marsden PV, Andrews SB. Network sampling and the network effects model, 1991. Unpublished manuscript, Harvard University.
  • 22
    Robins G, Pattison P, Woolcock J. Small and other worlds: global network structures from local processes. American Journal of Sociology 2005; 110:894936.
  • 23
    Erdös P, Rényi A. Random graphs. Publicationes Mathematicae 1959; 6:290297.
  • 24
    Holland P, Leinhardt S. An exponential family of probability-distributions for directed-graph. Journal of American Statistical Association 1981; 76:3350.
  • 25
    Wang W, Wong G. Stochastic blockmodels for directed graphs. Journal of the American Statistical Association 1987; 82:819.
  • 26
    Fineberg S, Wasserman S. Categorical data analysis of single sociometric relations. In Sociological Methodology. Jossey-Bass: San Francisco, 1981; 156192.
  • 27
    Holland P, Laskey K, Leinhardt S. Stochastic blockmodels: some first steps. Social Networks 1983; 5:109137.
  • 28
    Airoldi EM, Fienberg SE, Joutard CJ, Love TM. Hierarchical Bayesian mixed-membership models and latent pattern discovery. In Frontiers of Statistical Decision Making and Bayesian Analysis: In Honor of James O. Berger, Chen M-H, Dey DK, Müller P, Sun D, Ye K (eds). Springer-Verlag Inc: New York, 2010; 360375.
  • 29
    Choi D, Wolfe P, Airoldi E. Stochastic blockmodels with growing number of classes. Biometrika 2011. In press.
  • 30
    Frank O, Strauss D. Markov graphs. Journal of American Statistical Association 1986; 81:832842.
  • 31
    Wasserman S, Pattison P. Logit models and logistic regressions for social networks: I. An introduction to markov graphs and p*. Psychometrika 1996; 61:401425.
  • 32
    Hunter DR, Handcock MS. Inference in curved exponential family models for networks. Journal of Computational and Graphical Statistics 2006; 15:565583.
  • 33
    Snijders TAB. Statistical methods for network dynamics. In Proceedings of the XLIII Scientic Meeting, Italian Statistical Society, Luchini SR, et al. (ed.) Padova: CLEUP, Italy, 2006; 281296.
  • 34
    Strauss D, Ikeda M. Pseudolikelihood estimation for social networks. Journal of American Statistical Association 1990; 85:204212.
  • 35
    Van Duijn MAJ, Gile KJ, Handcock MS. A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models. Social Networks 2009; 31(1):5262.
  • 36
    Handcock MS, Robins GL, Snijders TAB, Moody J, Besag J. Assessing degeneracy in statistical models of social networks. Journal of American Statistical Association 2003; 76:3350.
  • 37
    Goodreau S. Advances in exponential random graph (p*) models applied to a large social network. Social Networks 2007; 29:231248.
  • 38
    Robins GL, Snijders TAB, Wang P, Handcock MS, Pattison PE. Recent developments in exponential random graph (p*) models for social networks. Social Networks 2007; 29(2):192215.
  • 39
    Duijn MV, Snijders TAB, Zijlstra B. P2: a random effects model with covariates for directed graphs. Statistica Neerlandica 2004; 58:234254.
  • 40
    Zijlstra BJH, Duijn MV, Snijders TAB. The multilevel p2 model: a random effects model for the analysis of multiple social networks. Methodology 2006; 2:4247.
  • 41
    Nowicki K, Snijders TAB. Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association 2001; 96(455):10771087.
  • 42
    Airoldi EM, Fienberg SE, Xing EP. Mixed membership stochastic blockmodels. Journal of Machine Learning Research 2008; 9:19812014.
  • 43
    Hoff PD, Raftery AE, Handcock MS. Latent space models for social networks analysis. Journal of American Statistical Association 2002; 97:10901098.
  • 44
    Handcock M, Raftery A, Tantrum J. Model-based clustering for social networks. Journal of the Royal Statistical Society Series A 2007; 170:301354.
  • 45
    Hoff PD. Bilinear mixed effects models for dyadic data. Journal of American Statistical Association 2005; 100:286295.
  • 46
    Hoff P. Modeling homophily and stochastic equivalence in symmetric relational data. In Advances in Neural Information Processing Systems, Vol. 20. MIT Press: Cambridge, Massachussets, 2008; 657664.
  • 47
    Raftery A, Niu X, Hoff P, Yeung K. Fast inference for the latent space network model using a case–control approximate likelihood. To appear: Journal of Computational and Graphical Statistics 2012.
  • 48
    Paul S, O'Malley AJ. Hierarchical longitudinal models of relationships in social networks. Under Review: Journal of the Royal Statistical Society, Series C 2012.
  • 49
    Hanneke S, Wenjie F, Xiang EP. Discrete Temporal models of Social Network. Electronic Journal of Statistics 2010; 4:585605. DOI: 10.1214/09-EJS548.
  • 50
    Hanneke S, Fu W, Xing EP. Discrete temporal models of social networks. Electronic Journal of Statistics 2010; 4:585605.
  • 51
    Krivitsky PN, Handcock MS. A separable model for dynamic networks. arXiv preprint 2010; 1011.1937v1[stat.ME].
  • 52
    Snijders T. Stochastic actor-oriented models for network change. Journal of Mathematical Sociology 1996; 21:149172.
  • 53
    Snijders TAB. The statistical evaluation of social network dynamics. In Sociological Methodology. Basil Blackwell: Boston, Massachussets, 2001; 361395.
  • 54
    Snijders TAB. Models for longitudinal social network data. In Models and Methods in Social Network Analysis. Cambridge University Press: Cambridge, United Kingdom, 2005; 215247.
  • 55
    Goldenberg A, Zheng AX, Fieberg SE, Airoldi EM. A survey of statistical network models. Foundations and Trends in Machine Learning 2009; 2:129233.
  • 56
    Huisman M, Van Duijn M. Software for statistical analysis of social networks. The Sixth International Conference on Logic and Methodology, Amsterdam, The Netherlands, 2004.
  • 57
    Huisman M, Van Duijn M. Software for social networks analysis. In Models and Methods in Social Network Analysis. Cambridge University Press: Cambridge, United Kingdom, 2005.
  • 58
    O'Malley AJ, Christakis NA. Longitudinal analysis of large social networks: estimating the effect of health traits on changes in friendship ties. Statistics in Medicine 2011; 30:950964.
  • 59
    Westveld AH, Hoff PD. A mixed effect model for longitudinal relational and network data, with applications to international trade and conflict. The Annals of Applied Statistics 2011; 5(2A):843872.
  • 60
    Steglich C, Snijders TAB, Pearson M. Dynamic networks and behavior: separating selection from influence. Sociological Methodology 2010; 40:329393.
  • 61
    Szabo G, Barabasi AL. Network effects in service usage. Arxiv preprint 2007. (Available from: http://lanl.arxiv.org/abs/physics/0611177) [Accessed on January 17, 2012].
  • 62
    Shalizi CR, Thomas AC. Homophily and contagion are generically confounded in observational social network studies. Sociological Methods & Research 2011; 40(2):211239.
  • 63
    Christakis N, Fowler J. The spread of obesity in a large social network over 32 years. New England Journal of Medicine 2007; 357:370379.
  • 64
    Thompson SK. Adaptive web sampling. Biometrics 2006; 62(4):12241234.
  • 65
    Thompson SK. Targeted random walk designs. Survey Methodology 2006; 32(1):1124.
  • 66
    Gile KJ. Improved inference for respondent-driven sampling data with application to HIV prevalence estimation. Journal of the American Statistical Association 2011; 106(493):135146.