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4. A Relational Event Approach to Modeling Behavioral Dynamics

  • 2017
  • OriginalPaper
  • Chapter
Published in:
Authors
Carter T. Butts
Christopher Steven Marcum
Published in
Group Processes
Publisher
Springer International Publishing

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Abstract

This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of relational event modeling, with an emphasis on models with piecewise constant hazards. We then discuss estimation for dyadic and more general relational event models using the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling, simulation, and analysis of relational data. Statnet packages are contributed by a team of volunteer developers, and are made freely available under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing platform that supports R (including Windows, Linux, and Mac).

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previous chapter Causal Inference Using Bayesian Networks
next chapter Text Mining Tutorial
Title
A Relational Event Approach to Modeling Behavioral Dynamics
Authors
Carter T. Butts
Christopher Steven Marcum
Copyright Year
2017
Book
Group Processes

Print ISBN: 978-3-319-48940-7

Electronic ISBN: 978-3-319-48941-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-48941-4_4
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