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

"It is rare to find a book that provides a nicely organized discussion of the approaches to evaluation, as well as hands-on information on managing evaluation, evaluation ethics, different evaluation philosophies, and utilization of evaluation. I especially liked the distinction among the various interventions that are the focus of evaluations, and the charts of the forms of evaluation. I also liked the focus on planning and diagnostic evaluation. The graphics are excellent, and Owen makes good use of inset boxes for examples. I would use the book in an introductory evaluation class to provide students with a roadmap of evaluation approaches and techniques and when and why to use them. This is one of only a few available texts that assemble techniques and approaches used in various countries across the world, and thus it should appeal to a wide audience."

-Debra J. Rog, Center for Evaluation and Program Improvement, Vanderbilt University

"This book breaks entirely new ground and, for the first time, offers social scientists a detailed methodological armamentarium for the analysis of dyadic data that appear in a broad range of research contexts. The development of original and creative solutions to some of the most vexing problems in dyadic research is presented in a clear, accessible manner by these talented authors. Dyadic Data Analysis is destined to become a classic, and will be essential reading for advanced students and researchers studying dyadic phenomena."

-Tom Malloy, Department of Psychology, Rhode Island College

"If any researcher (faculty or student) asked me for advice on dyadic data, I would send him or her to this book first. It provides clear definitions, accessible reviews of topics that appear in research journals, intuitive examples, and illustrations with computer code. The authors are to be commended for taking such difficult topics and communicating them in an accessible manner."

-Richard Gonzalez, Department of Psychology, University of Michigan

"A well-written and thoroughgoing discussion of issues and approaches in the analysis of dyadic data, written by leaders in the field....The book would be appropriate for advanced undergraduate social psychology methods classes, as well as graduate seminars. I strongly recommend this text to every social relations and social psychology researcher. I expect it will soon become a widely cited classic."

-Bruno D. Zumbo, Measurement, Evaluation, and Research Methodology Program, and Department of Statistics, University of British Columbia, Canada

"A wonderful addition to every researcher's tool chest for studying social relations and social interaction....What makes [the authors'] book so useful is the array of subtle issues they discuss, from when to treat dyadic members as distinguishable or as indistinguishable, to how to array data for dyadic analyses. The kinds of questions examined--from the minute to the sweeping--indicate that this book is written by people with substantial experience in social relations research."

-Joseph N. Cappella, Annenberg School for Communication, University of Pennsylvania

"An excellent, accessible, and instructive guide to dyadic data analysis. The authors clearly explain why interdependent data are problematic when approached with classical statistical techniques. More importantly, however, they enlighten the reader about the hidden treasures and opportunities that are inherent in dyadic data. This book provides a clear survey of various analytic techniques that researchers can use to ask and answer questions about the dynamics of interpersonal interactions, and it provides an engaging review of interdisciplinary applications of dyadic data designs."

-Todd D. Little, Department of Psychology and Schiefelbusch Institute for Life Span Studies, University of Kansas

1. Basic Definitions and Overview

Nonindependence

Basic Definitions

Data Organization

A Database of Dyadic Studies

2. The Measurement of Nonindependence

Interval Level of Measurement

Categorical Measures

Consequences of Ignoring Nonindependence

What Not to Do

Power Considerations

3. Analyzing Between- and Within-Dyads Independent Variables

Interval Outcome Measures and Categorical Independent Variables

Interval Outcome Measures and Interval Independent Variables

Categorical Outcome Variables

4. Using Multilevel Modeling to Study Dyads

Mixed-Model ANOVA

Multilevel-Model Equations

Multilevel Modeling with Maximum Likelihood

Adaptation of Multilevel Models to Dyadic Data

5. Using Structural Equation Modeling to Study Dyads

Steps in SEM

Confirmatory Factor Analysis

Path Analyses with Dyadic Data

SEM for Dyads with Indistinguishable Members

6. Tests of Correlational Structure and Differential Variance

Distinguishable Dyads

Indistinguishable Dyads

7. Analyzing Mixed Independent Variables: The Actor.Partner Interdependence Model

The Model

Conceptual Interpretation of Actor and Partner Effects

Estimation of the APIM: Indistinguishable Dyad Members

Estimation of the APIM: Distinguishable Dyads

Power and Effect Size Computation

Specification Error in the APIM

8. Social Relations Designs with Indistinguishable Members

The Basic Data Structures

Model

Details of an SRM Analysis

Model

Social Relations Analyses: An Example

9. Social Relations Designs with Roles

SRM Studies of Family Relationships

Design and Analysis of Studies

The Model

Application of the SRM with Roles Using Confirmatory Factor Analysis

The Four-Person Design

Illustration of the Four-Person Family Design

The Three-Person Design

Multiple Perspectives on Family Relationships

Means and Factor Score Estimation

Power and Sample Size

10. One-with-Many Designs

Design Issues

Measuring Nonindependence

The Meaning of Nonindependence in the One-with-Many Design

Univariate Analysis with Indistinguishable Partners

Univariate Estimation with Distinguishable Partners

The Reciprocal One-with-Many Design

11. Social Network Analysis

Definitions

The Representation of a Network

Network Measures

The p1

12. Dyadic Indexes

Item Measurement Issues

Measures of Profile Similarity

Mean and Variance of the Dyadic Index

Stereotype Accuracy

Differential Endorsement of the Stereotype

Pseudo-Couple Analysis

Idiographic versus Nomothetic Analysis

Illustration

13. Over-Time Analyses: Interval Outcomes

Cross-Lagged Regressions

Over-Time Standard APIM

Growth-Curve Analysis

Cross-Spectral Analysis

Nonlinear Dynamic Modeling

14. Over-Time Analyses: Dichotomous Outcomes

Sequential Analysis

Statistical Analysis of Sequential Data: Log-Linear Analysis

Statistical Analysis of Sequential Data: Multilevel Modeling

Event-History Analysis

15. Concluding Comments

Specialized Dyadic Models

Going Beyond the Dyad

Conceptual and Practical Issues

The Seven Deadly Sins of Dyadic Data Analysis

The Last Word

David A. Kenny, PhD, is Board of Trustees Professor in the Department of Psychology at the University of Connecticut, and he has also taught at Harvard University and Arizona State University. He served as first quantitative associate editor of Psychological Bulletin. Dr. Kenny was awarded the Donald Campbell Award from the Society of Personality and Social Psychology. He is the author of five books and has written extensively in the areas of mediational analysis, interpersonal perception, and the analysis of social interaction data.

Deborah A. Kashy, PhD, is Professor of Psychology at Michigan State University (MSU). She is currently senior associate editor of Personality and Social Psychology Bulletin and has also served as associate editor of Personal Relationships. In 2005 Dr. Kashy received the Alumni Outstanding Teaching Award from the College of Social Science at MSU. Her research interests include models of nonindependent data, interpersonal perception, close relationships, and effectiveness of educational technology.

William L. Cook, PhD, is Associate Director of Psychiatry Research at Maine Medical Center and Spring Harbor Hospital, and Clinical Associate Professor of Psychiatry at the University of Vermont College of Medicine. Originally trained as a family therapist, he has taken a lead in the dissemination of methods of dyadic data analysis to the study of normal and disturbed family systems. Dr. Cook.s contributions include the first application of the Social Relations Model to family data, the application of the Actor.Partner Interdependence Model to data from experimental trials of couple therapy, and the development of a method of standardized family assessment using the Social Relations Model.