Dyadic Data Analysis

Actor-Partner Interdependence and Multilevel Approaches

Author

Francisco Cardozo, PhD

Published

March 27, 2026

Overview

Analysis of dyadic data focuses on the interdependence between two individuals (e.g., couples, friends, siblings). We will explore methods to handle this non-independence and model the relationships between dyad members.

Learning Objectives

By the end of this lesson, you will be able to:

  1. Distinguish between distinguishable and indistinguishable dyads
  2. Identify sources of dyadic variability (between vs. within)
  3. Test for non-independence and compute the Intraclass Correlation (ICC)
  4. Fit multilevel models for dyadic data in R
  5. Understand and apply the Actor-Partner Interdependence Model (APIM)
  6. Implement the SEM approach for dyadic analysis

Topics

  • Distinguishable vs. Indistinguishable Dyads
  • Dyadic Variability (Between vs. Within)
  • Non-independence and Intraclass Correlation (ICC)
  • Multilevel Modeling for Dyads
  • Actor-Partner Interdependence Model (APIM)
  • Structural Equation Modeling (SEM) approach

Materials

TipSlides

Access the class presentation slides:

View Class Slides

WarningAssignment

Assignment #8: Estimating dyadic correlations via CFA and multilevel models. Due next week.

View Assignment

Readings

Required

  • Kenny, David & Kashy, Deborah & Cook, William & Simpson, Jeffry. (2006). Dyadic Data Analysis. [Pages 25-32 and Chapter 5]

Supplemental