Network estimation from time series and panel data

Open Access
Authors
Publication date 2022
Host editors
  • A.-M. Isvoranu
  • S. Epskamp
  • L. Waldorp
  • D. Borsboom
Book title Network Psychometrics with R
Book subtitle A Guide for Behavioral and Social Scientists
ISBN
  • 9780367628765
  • 9780367612948
ISBN (electronic)
  • 9781000541076
Series Research methods and statistics
Pages (from-to) 169-192
Publisher Abingdon: Routledge
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Amsterdam School of Communication Research (ASCoR)
  • Faculty of Law (FdR)
  • Faculty of Social and Behavioural Sciences (FMG) - Psychology Research Institute (PsyRes)
Abstract

This chapter discusses how to estimate graphical vector auto-regression (GVAR) network models from time series and panel data. The GVAR model can be used to estimate temporal networks (within-person relationships over time), contemporaneous networks (within-person relationships in the same window of measurement), and between-person networks (relationships between the means of persons in the data). The chapter explains how such network structures can be estimated using the R-packages graphicalVAR, psychonetrics, and mlVAR. The chapter concludes with a discussion of current practical and methodological challenges, including the power of N = 1 networks, heterogeneity, missing data, model assumptions, and the importance of identifying appropriate time scales.

Document type Chapter
Language English
Published at https://doi.org/10.4324/9781003111238-13
Published at https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=3024678&site=ehost-live&scope=site&ebv=EB&ppid=pp_169
Other links http://www.routledge.com/cw/Isvoranu https://www.scopus.com/pages/publications/85139633852
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