Dyadic longitudinal models: A critical review

Masumi Iida, Andrea Savord, Thomas Ledermann

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

In this review, we discuss the most commonly used models to analyze dyadic longitudinal data. We start the review with a definition of dyadic longitudinal data that allows relationship researchers to identify when these models might be appropriate. Then, we go on to describe the three major models commonly used when one has dyadic longitudinal data: the dyadic growth curve model (DGCM), the actor–partner interdependence model (APIM), and the common fate growth model (CFGM). We discuss when each model might be used and strengths and weaknesses of each model. We end with additional thoughts that focus on extensions to new methods being discussed in the literature, along with some of the challenges of collecting and analyzing dyadic longitudinal data that might be helpful for future dyadic researchers.

Original languageEnglish (US)
Pages (from-to)356-378
Number of pages23
JournalPersonal Relationships
Volume30
Issue number2
DOIs
StatePublished - Jun 2023

Keywords

  • actor–partner interdependence models
  • common fate growth modeling
  • dyadic growth curve model
  • longitudinal dyadic data analysis
  • multilevel modeling
  • structural equation modeling

ASJC Scopus subject areas

  • Social Psychology
  • Anthropology
  • Developmental and Educational Psychology
  • Life-span and Life-course Studies

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