Analyzing Mixed-Dyadic Data Using Structural Equation Models

James L. Peugh, David DiLillo, Jillian Panuzio

Research output: Contribution to journalArticlepeer-review

79 Scopus citations


Mixed-dyadic data, collected from distinguishable (nonexchangeable) or indistinguishable (exchangeable) dyads, require statistical analysis techniques that model the variation within dyads and between dyads appropriately. The purpose of this article is to provide a tutorial for performing structural equation modeling analyses of cross-sectional and longitudinal models for mixed independent variable dyadic data, and to clarify questions regarding various dyadic data analysis specifications that have not been addressed elsewhere. Artificially generated data similar to the Newlywed Project and the Swedish Adoption Twin Study on Aging were used to illustrate analysis models for distinguishable and indistinguishable dyads, respectively. Due to their widespread use among applied researchers, the AMOS and Mplus statistical analysis software packages were used to analyze the dyadic data structural equation models illustrated here. These analysis models are presented in sufficient detail to allow researchers to perform these analyses using their preferred statistical analysis software package.

Original languageEnglish (US)
Pages (from-to)314-337
Number of pages24
JournalStructural Equation Modeling
Issue number2
StatePublished - Apr 2013


  • distinguishable
  • dyadic
  • exchangeable
  • indistinguishable
  • mixed

ASJC Scopus subject areas

  • General Decision Sciences
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)


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