Dyadic data in family science

Christine M. Proulx, Brian G. Ogolsky

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Inherent in the study of families and family theorizing is an interest in multiple, interdependent members of the family. The notion of dyads (sometimes referred to as "matched pairs"; Wheeler et al., 2018) and the need to examine them is anchored in the field of sociology and early conceptualizations of the dyad as a pair with a history of "patterned mutual interaction" (Becker & Useem, 1942). Theoretical interest in the dyad as an interdependent pair existed well before adequate statistical methods for analyzing matched pairs as the unit of analysis were available. Now, there are multiple options for analyzing dyadic data, including repeated measures ANOVA, the intra-class correlation, structural equation modeling, actor-partner interdependence models, mixture models, and multilevel modeling, among others. In this chapter, we highlight some of these methods and the research questions to which they are best suited, address the unique challenges and opportunities inherent in working with dyadic data, and offer our suggestions for the future of dyadic data analysis and design in family science.

Original languageEnglish (US)
Title of host publicationSourcebook of Family Theories and Methodologies
Subtitle of host publicationA Dynamic Approach
PublisherSpringer
Pages359-368
Number of pages10
ISBN (Electronic)9783030920029
ISBN (Print)9783030920012
DOIs
StatePublished - Nov 7 2022

ASJC Scopus subject areas

  • General Psychology
  • General Social Sciences
  • General Medicine

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