Using the Relational Event Model (REM)
|Dates:||10 October 2016|
|What is it:||Workshop|
|Organiser:||Cathie Marsh Institute for Social Research|
|Speaker:||Dr Mark Tranmer|
The course will explain how the Relational Event Model (REM) may be used to investigate patterns in ordered or timed sequences of actions.We begin by giving some examples for which ordered sequences of timed data may be collected, including patterns of behaviour of individuals over time, and interactions in a network of individuals over time.
We then introduce the REM in the context of other related methods, such as survival analysis, and also in the context of other ways of looking at sequences of actions, such as sequence analysis. We explain the importance of taking into account the way in which the ordered or timed data were collected, and the actions that were observable at each point in the sequence, when analysing it, and explain how this can be achieved.
Next, we explain how an R package called informR can enable us to prepare ordered or timed data for analysis with a REM. Data preparation with InformR allows us to take into account the way in which the data were collected, and the actions that are observable at each point in the sequence. InformR also allows us to create “sequence statistics” to allow us to investigate particular patterns in the timed or ordered sequence of actions that may be of particular substantive interest.Finally we explain how relevent, an R package, can be used to fit REMs to ordered or timed sequence data. We give examples, and explain how the results of a REM analysis that has been carried out using relevent can be interpreted.
- Introduce the Relational Event Model (REM) in the context of existing models and approaches. Explain the advantages of the REM over other methods, given particular substantive aims and data.
- Explain the need to take into account the data collection mechanism in the analysis of ordered or timed sequences of actions.
- Provide hands-on training in the use of informR (an R package) to prepare the ordered or timed sequence data for analysis with a REM. This includes setting up “sequence statistics”.
- Provide hands-on training in the use of relevent (an R package) to fit Relational Event Models (REMs).
- Understand how to interpret the results of such analyses.
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Travel and Contact Information
Humanities Bridgeford Street