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Network dynamics with a nested node set: Sociability in seven villages in Senegal

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  • Tom A.B. Snijders
  • Malick Faye
  • Julien Brailly

Abstract

We propose two complementary ways to deal with a nesting structure in the node set of a network—such a structure may be called a multilevel network, with a node set consisting of several groups. First, within‐group ties are distinguished from between‐group ties by considering them as two distinct but interrelated networks. Second, effects of nodal variables are differentiated according to the levels of the nesting structure, to prevent ecological fallacies. This is elaborated in a study of two repeated observations of a sociability network in seven villages in Senegal, analyzed using the Stochastic Actor‐oriented Model.

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  • Tom A.B. Snijders & Malick Faye & Julien Brailly, 2020. "Network dynamics with a nested node set: Sociability in seven villages in Senegal," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 300-323, August.
  • Handle: RePEc:bla:stanee:v:74:y:2020:i:3:p:300-323
    DOI: 10.1111/stan.12208
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    References listed on IDEAS

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    1. Hollway, James & Lomi, Alessandro & Pallotti, Francesca & Stadtfeld, Christoph, 2017. "Multilevel social spaces: The network dynamics of organizational fields," Network Science, Cambridge University Press, vol. 5(2), pages 187-212, June.
    2. Schweinberger, Michael & Snijders, Tom A.B., 2007. "Markov models for digraph panel data: Monte Carlo-based derivative estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4465-4483, May.
    3. Cornelius Fritz & Michael Lebacher & Göran Kauermann, 2020. "Tempus volat, hora fugit: A survey of tie‐oriented dynamic network models in discrete and continuous time," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 275-299, August.
    4. Snijders, Tom A.B. & Lomi, Alessandro, 2019. "Beyond homophily: Incorporating actor variables in statistical network models," Network Science, Cambridge University Press, vol. 7(1), pages 1-19, March.
    5. Viviana Amati & Felix Schönenberger & Tom A. B. Snijders, 2019. "Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 1068-1096, December.
    6. Pavel N. Krivitsky & Mark S. Handcock, 2014. "A separable model for dynamic networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 29-46, January.
    7. De Benedictis, Luca & Vitale, Maria Prosperina & Wasserman, Stanley, 2015. "Examining the literature on “Networks in Space and in Time.†An introduction," Network Science, Cambridge University Press, vol. 3(1), pages 1-17, March.
    8. C Matias & T Rebafka & F Villers, 2018. "A semiparametric extension of the stochastic block model for longitudinal networks," Biometrika, Biometrika Trust, vol. 105(3), pages 665-680.
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    Cited by:

    1. Simpson, Cohen R., 2022. "Social support and network formation in a small-scale horticulturalist population," LSE Research Online Documents on Economics 116694, London School of Economics and Political Science, LSE Library.

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