Interpersonal phenomena such as attachment, conflict, person perception, learning, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, parent and child, teacher and student, or doctor and patient, to name just a few. Rich examples from psychology and across the behavioral and social sciences help build the researcher's ability to conceptualize relationship processes; model and test for actor effects, partner effects, and relationship effects; and model and control for the statistical interdependence that can exist between partners.

Providing a solid grasp of the many facets of dyadic analysis, the book provides a taxonomy of dyadic designs and addresses:

• How to design an appropriate dyadic study to address a particular research question
• Nonindependence: what it is and how to measure it
• Ways to model and test for actor effects, partner effects, and relationship effects
• Strategies for analyzing each dyad in a study with multiple outcome variables
• The use of multilevel modeling and structural equation modeling in the estimation of dyadic models
• Organization and documentation of dyadic data files
• The "Seven Deadly Sins" of dyadic data analysis and how to avoid them
• The companion website provides clarifications, elaborations, corrections, and data and files for each chapter.

This title is part of the Methodology in the Social Sciences Series, edited by Todd D. Little.