Methods and Software for the Multilevel Social Relations Model: A Tutorial

Jeremy Koster, George Leckie, Brandy Aven, Christopher Charlton

Research output: Contribution to journalArticle (Academic Journal)

100 Downloads (Pure)

Abstract

This tutorial demonstrates the estimation and interpretation of the Multilevel Social Relations Model for dyadic data. The Social Relations Model is appropriate for data structures in which individuals appear multiple times as both the source and recipient of dyadic outcomes. Estimated using Stat-JR statistical software, the models are fitted to multiple outcome types: continuous, count, and binary outcomes. In addition, models are demonstrated for dyadic data from a single group and from multiple groups. The modeling approaches are illustrated via a series of case studies, and the data and software to replicate these analyses are available as supplemental files.
Original languageEnglish
JournalarXiv
Issue number41
Publication statusAccepted/In press - 22 Jul 2019

Research Groups and Themes

  • SoE Centre for Multilevel Modelling

Keywords

  • stat.AP
  • stat.ME

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