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Multilevel longitudinal analysis of social networks
Stochastic actor-oriented models (SAOMs) are a modelling framework for analysing network dynamics using network panel data. This paper extends the SAOM to the analysis of multilevel network panels through a random coefficient model, estimated with a Bayesian approach. The proposed model allows testi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10376442/ https://www.ncbi.nlm.nih.gov/pubmed/37521824 http://dx.doi.org/10.1093/jrsssa/qnac009 |
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author | Koskinen, Johan Snijders, Tom A B |
author_facet | Koskinen, Johan Snijders, Tom A B |
author_sort | Koskinen, Johan |
collection | PubMed |
description | Stochastic actor-oriented models (SAOMs) are a modelling framework for analysing network dynamics using network panel data. This paper extends the SAOM to the analysis of multilevel network panels through a random coefficient model, estimated with a Bayesian approach. The proposed model allows testing theories about network dynamics, social influence, and interdependence of multiple networks. It is illustrated by a study of the dynamic interdependence of friendship networks and minor delinquency. Data were available for 126 classrooms in the first year of secondary school, of which 82 were used, containing relatively few missing data points and having not too much network turnover. |
format | Online Article Text |
id | pubmed-10376442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103764422023-07-29 Multilevel longitudinal analysis of social networks Koskinen, Johan Snijders, Tom A B J R Stat Soc Ser A Stat Soc Original Article Stochastic actor-oriented models (SAOMs) are a modelling framework for analysing network dynamics using network panel data. This paper extends the SAOM to the analysis of multilevel network panels through a random coefficient model, estimated with a Bayesian approach. The proposed model allows testing theories about network dynamics, social influence, and interdependence of multiple networks. It is illustrated by a study of the dynamic interdependence of friendship networks and minor delinquency. Data were available for 126 classrooms in the first year of secondary school, of which 82 were used, containing relatively few missing data points and having not too much network turnover. Oxford University Press 2023-01-23 /pmc/articles/PMC10376442/ /pubmed/37521824 http://dx.doi.org/10.1093/jrsssa/qnac009 Text en © (RSS) Royal Statistical Society 2023. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Koskinen, Johan Snijders, Tom A B Multilevel longitudinal analysis of social networks |
title | Multilevel longitudinal analysis of social networks |
title_full | Multilevel longitudinal analysis of social networks |
title_fullStr | Multilevel longitudinal analysis of social networks |
title_full_unstemmed | Multilevel longitudinal analysis of social networks |
title_short | Multilevel longitudinal analysis of social networks |
title_sort | multilevel longitudinal analysis of social networks |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10376442/ https://www.ncbi.nlm.nih.gov/pubmed/37521824 http://dx.doi.org/10.1093/jrsssa/qnac009 |
work_keys_str_mv | AT koskinenjohan multilevellongitudinalanalysisofsocialnetworks AT snijderstomab multilevellongitudinalanalysisofsocialnetworks |