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Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality
Network analysis of ESM data has become popular in clinical psychology. In this approach, discrete-time (DT) vector auto-regressive (VAR) models define the network structure with centrality measures used to identify intervention targets. However, VAR models suffer from time-interval dependency. Cont...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021117/ https://www.ncbi.nlm.nih.gov/pubmed/34165691 http://dx.doi.org/10.1007/s11336-021-09767-0 |
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author | Ryan, Oisín Hamaker, Ellen L. |
author_facet | Ryan, Oisín Hamaker, Ellen L. |
author_sort | Ryan, Oisín |
collection | PubMed |
description | Network analysis of ESM data has become popular in clinical psychology. In this approach, discrete-time (DT) vector auto-regressive (VAR) models define the network structure with centrality measures used to identify intervention targets. However, VAR models suffer from time-interval dependency. Continuous-time (CT) models have been suggested as an alternative but require a conceptual shift, implying that DT-VAR parameters reflect total rather than direct effects. In this paper, we propose and illustrate a CT network approach using CT-VAR models. We define a new network representation and develop centrality measures which inform intervention targeting. This methodology is illustrated with an ESM dataset. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11336-021-09767-0. |
format | Online Article Text |
id | pubmed-9021117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-90211172022-05-06 Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality Ryan, Oisín Hamaker, Ellen L. Psychometrika Application Reviews and Case Studies Network analysis of ESM data has become popular in clinical psychology. In this approach, discrete-time (DT) vector auto-regressive (VAR) models define the network structure with centrality measures used to identify intervention targets. However, VAR models suffer from time-interval dependency. Continuous-time (CT) models have been suggested as an alternative but require a conceptual shift, implying that DT-VAR parameters reflect total rather than direct effects. In this paper, we propose and illustrate a CT network approach using CT-VAR models. We define a new network representation and develop centrality measures which inform intervention targeting. This methodology is illustrated with an ESM dataset. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11336-021-09767-0. Springer US 2021-06-24 2022 /pmc/articles/PMC9021117/ /pubmed/34165691 http://dx.doi.org/10.1007/s11336-021-09767-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Application Reviews and Case Studies Ryan, Oisín Hamaker, Ellen L. Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality |
title | Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality |
title_full | Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality |
title_fullStr | Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality |
title_full_unstemmed | Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality |
title_short | Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality |
title_sort | time to intervene: a continuous-time approach to network analysis and centrality |
topic | Application Reviews and Case Studies |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021117/ https://www.ncbi.nlm.nih.gov/pubmed/34165691 http://dx.doi.org/10.1007/s11336-021-09767-0 |
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