A primer on multilevel mediation models for egocentric social network data

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


The substantial increase in nested data such as egocentric network data pose unique challenges to researchers, including how to adequately model the mechanisms and processes in which hypothesized effects operates within the complex interdependencies among social actors. While there is a growing interest in identifying the causal mechanisms and their contingencies using such nested structured data, the direct application of principles of (moderated) mediation analysis within traditional multilevel modeling framework is ambiguous and controversial. In this article, I provide a tutorial illustrating an approach to assessing mediation hypotheses based on path-analytic framework popularized by Hayes (2013). Focusing on estimation and inference of indirect effects with regard to nested data structure, I provide examples of the analysis within the context of egocentric network data, and illustrate implementation using Mplus software.

Original languageEnglish
Pages (from-to)1-24
Number of pages24
JournalCommunication Methods and Measures
Issue number1
Publication statusPublished - 2018 Jan 2

Bibliographical note

Publisher Copyright:
©, Published with license by Taylor & Francis. © 2018 Hyunjin Song.

All Science Journal Classification (ASJC) codes

  • Communication


Dive into the research topics of 'A primer on multilevel mediation models for egocentric social network data'. Together they form a unique fingerprint.

Cite this