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

TL;DR

This tutorial explains how to estimate and interpret the Multilevel Social Relations Model for dyadic data using Stat-JR software, covering various outcome types and data structures through case studies.

Contribution

It provides a comprehensive tutorial on applying the Multilevel Social Relations Model with practical software and case studies, enhancing understanding and implementation.

Findings

Effective modeling of dyadic data with multiple outcome types

Application to single-group and multi-group data structures

Availability of data and software for replication

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.