Estimating Policy Effects in a Social Network with Independent Set Sampling
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[1] M. Morris,et al. Respondent-Driven Sampling: a Sampling Method for Hard-to-Reach Populations and Beyond , 2022, Current Epidemiology Reports.
[2] Karoline S. Rogge,et al. Interplay of policy experimentation and institutional change in sustainability transitions: The case of mobility as a service in Finland , 2022, Research Policy.
[3] Tassilo Schwarz,et al. Randomized Controlled Trials Under Influence: Covariate Factors and Graph-Based Network Interference , 2021, ArXiv.
[4] Kristof De Witte,et al. Policy evaluation and efficiency: a systematic literature review , 2021, Int. Trans. Oper. Res..
[5] Meng Li,et al. The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag , 2021 .
[6] E. Terán,et al. Application of a Susceptible, Infectious, and/or Recovered (SIR) Model to the COVID-19 Pandemic in Ecuador , 2020, Frontiers in Applied Mathematics and Statistics.
[7] Davide Viviano,et al. Policy design in experiments with unknown interference , 2020, 2011.08174.
[8] Johan Ugander,et al. Randomized graph cluster randomization , 2020, Journal of Causal Inference.
[9] I. Lee,et al. A Longitudinal Network Analysis of Intergovernmental Collaboration for Local Economic Development , 2020, Urban Affairs Review.
[10] Koen Jochmans,et al. Peer effects and endogenous social interactions , 2020, 2008.07886.
[11] Improving Governance with Policy Evaluation , 2020, OECD Public Governance Reviews.
[12] L. Chew,et al. Modelling Singapore COVID-19 pandemic with a SEIR multiplex network model , 2020, Scientific Reports.
[13] S. H. Khasteh,et al. A survey on exponential random graph models: an application perspective , 2020, PeerJ Comput. Sci..
[14] J. Grimshaw,et al. The ethical challenges raised in the design and conduct of pragmatic trials: an interview study with key stakeholders , 2019, Trials.
[15] S. Borrás,et al. Towards system oriented innovation policy evaluation? Evidence from EU28 member states , 2019, Research Policy.
[16] Per Block,et al. Forms of Dependence: Comparing SAOMs and ERGMs From Basic Principles , 2019 .
[17] E. Airoldi,et al. A systematic investigation of classical causal inference strategies under mis-specification due to network interference , 2018, 1810.08259.
[18] Anita M. M. Liu,et al. The evolution of government sponsored collaboration network and its impact on innovation: A bibliometric analysis in the Chinese solar PV sector , 2018, Research Policy.
[19] J. Locascio,et al. Randomised controlled trials – the gold standard for effectiveness research , 2018, BJOG : an international journal of obstetrics and gynaecology.
[20] Howard White,et al. Impact Evaluation of Development Interventions: A Practical Guide , 2017 .
[21] Ida Johnsson,et al. Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach , 2017, Review of Economics and Statistics.
[22] Edoardo M. Airoldi,et al. Detecting Network Effects: Randomizing Over Randomized Experiments , 2017, KDD.
[23] Douglas D. Heckathorn,et al. Network Sampling: From Snowball and Multiplicity to Respondent-Driven Sampling , 2017 .
[24] Edoardo Airoldi,et al. Limitations of Design-based Causal Inference and A/B Testing under Arbitrary and Network Interference , 2017, Sociological Methodology.
[25] J. Onnela,et al. Leveraging contact network structure in the design of cluster randomized trials , 2016, Clinical trials.
[26] Laura B. Rawlings,et al. Impact Evaluation in Practice, Second Edition , 2016 .
[27] Arnaud Vaganay. Cluster Sampling Bias in Government-Sponsored Evaluations: A Correlational Study of Employment and Welfare Pilots in England , 2016, PloS one.
[28] David R. Schaefer,et al. How Initial Prevalence Moderates Network-based Smoking Change , 2016, Journal of health and social behavior.
[29] A. Morrison,et al. The Dynamics of Technical and Business Knowledge Networks in Industrial Clusters: Embeddedness, Status, or Proximity? , 2016 .
[30] Julian TszKin Chan. Snowball Sampling and Sample Selection in a Social Network , 2015, The Econometrics of Networks.
[31] Jukka-Pekka Onnela,et al. Incorporating Contact Network Structure in Cluster Randomized Trials , 2015, Scientific Reports.
[32] Larry L Orr,et al. 2014 Rossi Award Lecture , 2015, Evaluation review.
[33] Charlotte C. Greenan,et al. Diffusion of innovations in dynamic networks , 2015 .
[34] Dean Eckles,et al. Design and Analysis of Experiments in Networks: Reducing Bias from Interference , 2014, ArXiv.
[35] A. Zaslavsky,et al. Estimating Peer Effects in Longitudinal Dyadic Data Using Instrumental Variables , 2014, Biometrics.
[36] S. Gupta,et al. Separating homophily and peer influence with latent space , 2013 .
[37] Jie Tang,et al. Influence Maximization in Dynamic Social Networks , 2013, 2013 IEEE 13th International Conference on Data Mining.
[38] Elisa Giuliani,et al. Network dynamics in regional clusters: Evidence from Chile , 2013 .
[39] Pili Hu,et al. A Survey and Taxonomy of Graph Sampling , 2013, ArXiv.
[40] Jon M. Kleinberg,et al. Graph cluster randomization: network exposure to multiple universes , 2013, KDD.
[41] Daniel K. N. Johnson,et al. Viral Economics: An Epidemiological Model of Knowledge Diffusion in Economics , 2011 .
[42] Bruce A. Desmarais,et al. Statistical Inference for Valued-Edge Networks: The Generalized Exponential Random Graph Model , 2011, PloS one.
[43] Laura B. Rawlings,et al. Impact Evaluation in Practice: Second Edition , 2010 .
[44] Martin A. Nowak,et al. Infectious Disease Modeling of Social Contagion in Networks , 2010, PLoS Comput. Biol..
[45] Yannis M. Ioannides,et al. Identification of Social Interactions , 2010 .
[46] C. Steglich,et al. DYNAMIC NETWORKS AND BEHAVIOR: SEPARATING SELECTION FROM INFLUENCE: separating selection from influence , 2010 .
[47] Cosma Rohilla Shalizi,et al. Homophily and Contagion Are Generically Confounded in Observational Social Network Studies , 2010, Sociological methods & research.
[48] Giacomo De Giorgi,et al. Identification of Social Interactions through Partially Overlapping Peer Groups , 2010 .
[49] Arun Sundararajan,et al. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks , 2009, Proceedings of the National Academy of Sciences.
[50] D. Watts,et al. Origins of Homophily in an Evolving Social Network1 , 2009, American Journal of Sociology.
[51] Hong Cheng,et al. Graph Clustering Based on Structural/Attribute Similarities , 2009, Proc. VLDB Endow..
[52] Santo Fortunato,et al. Community detection in graphs , 2009, ArXiv.
[53] Bryan S. Graham,et al. Identifying Social Interactions Through Conditional Variance Restrictions , 2008 .
[54] Jean-Loup Guillaume,et al. Fast unfolding of communities in large networks , 2008, 0803.0476.
[55] Lung-fei Lee,et al. Identification and estimation of econometric models with group interactions, contextual factors and fixed effects , 2007 .
[56] Peng Wang,et al. Recent developments in exponential random graph (p*) models for social networks , 2007, Soc. Networks.
[57] Tom A. B. Snijders,et al. Markov models for digraph panel data: Monte Carlo-based derivative estimation , 2007, Comput. Stat. Data Anal..
[58] Bernard Fortin,et al. Identification of Peer Effects through Social Networks , 2007, SSRN Electronic Journal.
[59] Luciano Rossoni. Models and methods in social network analysis , 2006 .
[60] Laurent Davezies,et al. Identification of Peer Effects Using Group Size Variation , 2006, SSRN Electronic Journal.
[61] S. Berg. Snowball Sampling—I , 2006 .
[62] Eric P. Xing,et al. Discrete Temporal Models of Social Networks , 2006, SNA@ICML.
[63] Bryan S. Graham,et al. Identification and estimation of the linear-in-means model of social interactions , 2005 .
[64] A. Kishk. Method of Moments , 2005 .
[65] Jon Kleinberg,et al. Maximizing the spread of influence through a social network , 2003, KDD '03.
[66] Peter D. Hoff,et al. Latent Space Approaches to Social Network Analysis , 2002 .
[67] M. McPherson,et al. Birds of a Feather: Homophily in Social Networks , 2001 .
[68] Robert Huggins,et al. Inter-firm network policies and firm performance: evaluating the impact of initiatives in the United Kingdom , 2001 .
[69] W. Brock,et al. Interactions-Based Models , 2000 .
[70] J. Wooldridge. Introductory Econometrics: A Modern Approach , 1999 .
[71] Jaikumar Radhakrishnan,et al. Greed is good: Approximating independent sets in sparse and bounded-degree graphs , 1997, Algorithmica.
[72] S. Wasserman,et al. Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp , 1996 .
[73] T. Valente,et al. Network models of the diffusion of innovations , 1995, Comput. Math. Organ. Theory.
[74] C. Manski. Identification of Endogenous Social Effects: The Reflection Problem , 1993 .
[75] G. Yin. On extensions of Polyak's averaging approach to stochastic approximation , 1991 .
[76] D. Ruppert,et al. Efficient Estimations from a Slowly Convergent Robbins-Monro Process , 1988 .
[77] G. Maddala. Limited-dependent and qualitative variables in econometrics: Introduction , 1983 .
[78] Russell Heikes,et al. Misleading indicators: The limitations of multiple linear regression in formulation of policy recommendations , 1981 .
[79] P. Sweetnam,et al. Statistical problems in studying the relative specificities of association between environmental agents and different diseases: a solution suggested. , 1979, International journal of epidemiology.
[80] Mark S. Granovetter. Threshold Models of Collective Behavior , 1978, American Journal of Sociology.
[81] J. Enns. THE RESPONSE OF STATE HIGHWAY EXPENDITURES AND REVENUES TO FEDERAL GRANTS-IN-AID , 1974 .
[82] Mario Osvin Pavčević,et al. Introduction to graph theory , 1973, The Mathematical Gazette.
[83] Yong Hyo Cho,et al. A multiple regression model for the measurement of the public policy impact on big city crime , 1972 .
[84] E. Rogers,et al. Diffusion of innovations , 1964, Encyclopedia of Sport Management.
[85] H. Robbins. A Stochastic Approximation Method , 1951 .
[86] W. O. Kermack,et al. A contribution to the mathematical theory of epidemics , 1927 .
[87] Experimental and Quasi-Experimental , 2023 .
[88] A. Flache,et al. The development of peer networks and academic performance in learning communities in higher education , 2022, Learning and Instruction.
[89] Abdessadek Tikniouine,et al. A comprehensive literature review on community detection: Approaches and applications , 2019, ANT/EDI40.
[90] June. Evaluating Complex Health Interventions : A Guide to Rigorous Research Designs June 2017 , 2017 .
[91] Tom A. B. Snijders,et al. Siena: Statistical Modeling of Longitudinal Network Data , 2014, Encyclopedia of Social Network Analysis and Mining.
[92] E. Tamer,et al. Some Interpretation of the Linear-In-Means Model of Social Interactions , 2014 .
[93] Tyler J. VanderWeele,et al. Social Networks and Causal Inference , 2013 .
[94] Stephen H Bell,et al. External Validity in Policy Evaluations that Choose Sites Purposively. , 2013, Journal of policy analysis and management : [the journal of the Association for Public Policy Analysis and Management].
[95] J. Pacheco,et al. The Social Contagion Model: Exploring the Role of Public Opinion on the Diffusion of Antismoking Legislation across the American States , 2012 .
[96] Dennis Epple,et al. Peer Effects in Education: A Survey of the Theory and Evidence , 2011 .
[97] Tom A. B. Snijders,et al. Introduction to stochastic actor-based models for network dynamics , 2010, Soc. Networks.
[98] T. Snijders,et al. Modeling the Coevolution of Networks and Behavior , 2007 .
[99] Kees van Montfort,et al. Longitudinal models in the behavioral and related sciences , 2007 .
[100] Tom A. B. Snijders,et al. Statistical Methods for Network Dynamics , 2006 .
[101] Tom A. B. Snijders,et al. Manual for SIENA version 2.1 , 2005 .
[102] T. Snijders. Models for longitudinal network datain , 2005 .
[103] T. Snijders. The statistical evaluation of social network dynamics , 2001 .
[104] M. McPherson,et al. BIRDS OF A FEATHER: Homophily , 2001 .
[105] Philippe Flajolet,et al. Adaptive Sampling , 1997 .
[106] T. Valente. Social network thresholds in the diffusion of innovations , 1996 .
[107] Jonathan R. Cole,et al. Fair Science: Women in the Scientific Community , 1987 .
[108] R. Radner,et al. Graduation, Graduate School Attendance, and Investments in College Training. , 1976 .
[109] HighWire Press. Proceedings of the Royal Society of London. Series A, Containing papers of a mathematical and physical character , 1934 .
[110] Tom Broekel,et al. Papers in Evolutionary Economic Geography # 19 . 27 A shot in the dark ? Policy influence on cluster networks , 2022 .