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.
"Everyone who studies interpersonal processes should have this book
on their shelves. Researchers following the analytical strategies
laid out in this book need only to cite this book and its authors
to validate their analyses. In addition, the authors describe the
analyses under various kinds of conditions (for example,
distinguishable versus nondistinguishable dyads), using different
estimation techniques (ordinary least squares, maximum likelihood,
etc.) and different software packages."--Linda Albright, Westfield
State 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, University of Michigan
"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, University of Kansas
"A wonderful addition to every researcher's tool chest for studying
social relations and social interaction. The authors provide a
systematic treatment of a wide variety of statistical and
methodological issues that arise in handling research data gathered
in the context of two-person interactions. What makes their 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. Of special value, the authors provide useful
guidance on the question of nonindependence by showing how the
issue can be treated both within mixed models from the analysis of
variance and in newer multilevel models. They do not avoid adding
the complication of replicated observations, providing a book that
ultimately covers nearly all the complexities of analyzing
two-person social relations data. I predict this book will be a
long-lived reference tool that all serious researchers in social
relations will consult regularly."--Joseph N. Cappella, University
of Pennsylvania
"This is a well-written and thoroughgoing discussion of issues and
approaches in the analysis of dyadic data, written by leaders in
the field. Dyadic data is a commonly found data structure in social
psychology and social relations research. The authors describe and
demonstrate several statistical methods, including multilevel and
structural equation modeling approaches. 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, University of British Columbia "I have relied on the work of
Kenny and his colleagues for many years. For anyone who studies
family and relationships and who wants to stay up to date on the
most effective ways to analyze quantitative data, this book is a
'must read.'"--Suzanne Bartle-Haring, PhD, Director, Couple and
Family Therapy Program, The Ohio State University - It will help
researchers to formulate new ways of addressing old research
questions in a more elegant and comprehensive manner....Destined to
become a classic methodology text and will hold valued space on the
bookshelves of methodologists and researchers of social concerns.
--Journal of Social and Clinical Psychology, 7/30/2006ƒƒ An
important source for any social scientist who has ever analyzed
data involving pairs of people. Journal editors and reviewers are
also recommended to know the contents of this book, because it will
likely result in new requirements for publishing dyadic research
that are essential as reliability and effect-size....[A] clear and
purposeful text for detailed how-to instructions on specific
analytical techniques....Kenny et al. make an invaluable
contribution by walking readers through ANOVA, SEM, regression, and
time-series analyses involving dyads, complete with SPSS and SAS
syntax....The book ends with an eye-opening summary of 'the seven
deadly sins of dyadic data analysis' (p. 421) that may serve as an
excellent starting point for readers with immediate analytic
concerns....Thorough, comprehensive, and clear. --Journal of
Anthropological Research, 7/30/2006ƒƒ By providing readers with a
well-written, nontechnical, description of various forms of
interdependence and how they can be quantitatively analyzed, the
authors make a tremendous advancement of our field. Simply put,
this book has the potential to drastically advance the ways that
researchers conceptualize, design studies, and analyze data
involving interdependent processes....The most important
contribution of this book lies in the fact that it is the first
comprehensive treatment of how researchers can quantitatively
analyze various patterns of interdependent data....The book is
exceptionally well written. The authors have clearly made great
efforts to ensure that the book is straightforward and accessible
by writing in an extremely clear and engaging manner....I consider
this book essential reading for any psychologist who claims to have
adequate training in data analysis....Valuable reading both early
in psychologists' training, perhaps immediately after introductory
courses in multivariate statistics, and later in psychologists'
training after they have more exposure to advanced quantitative
methods....More seasoned researchers will also find this book
valuable and may even wish this book had been available earlier in
their careers....This book has the very real possibility of
sparking an important change in how researchers conceptualize,
study, and quantitatively analyze interdependent processes....I
expect that this book will have a substantial impact on the field
and highly recommend it to all psychologists who study
interdependent phenomena. --PsycCRITIQUES, 7/30/2006
"Everyone who studies interpersonal processes should have this book
on their shelves. Researchers following the analytical strategies
laid out in this book need only to cite this book and its authors
to validate their analyses. In addition, the authors describe the
analyses under various kinds of conditions (for example,
distinguishable versus nondistinguishable dyads), using different
estimation techniques (ordinary least squares, maximum likelihood,
etc.) and different software packages."--Linda Albright, Westfield
State 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, University of Michigan
"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, University of Kansas
"A wonderful addition to every researcher's tool chest for studying
social relations and social interaction. The authors provide a
systematic treatment of a wide variety of statistical and
methodological issues that arise in handling research data gathered
in the context of two-person interactions. What makes their 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. Of special value, the authors provide useful
guidance on the question of nonindependence by showing how the
issue can be treated both within mixed models from the analysis of
variance and in newer multilevel models. They do not avoid adding
the complication of replicated observations, providing a book that
ultimately covers nearly all the complexities of analyzing
two-person social relations data. I predict this book will be a
long-lived reference tool that all serious researchers in social
relations will consult regularly."--Joseph N. Cappella, University
of Pennsylvania
"This is a well-written and thoroughgoing discussion of issues and
approaches in the analysis of dyadic data, written by leaders in
the field. Dyadic data is a commonly found data structure in social
psychology and social relations research. The authors describe and
demonstrate several statistical methods, including multilevel and
structural equation modeling approaches. 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, University of British Columbia "I have relied on the work of
Kenny and his colleagues for many years. For anyone who studies
family and relationships and who wants to stay up to date on the
most effective ways to analyze quantitative data, this book is a
'must read.'"--Suzanne Bartle-Haring, PhD, Director, Couple and
Family Therapy Program, The Ohio State University - It will help
researchers to formulate new ways of addressing old research
questions in a more elegant and comprehensive manner....Destined to
become a classic methodology text and will hold valued space on the
bookshelves of methodologists and researchers of social concerns.
--Journal of Social and Clinical Psychology, 7/30/2006Æ’Æ’ An
important source for any social scientist who has ever analyzed
data involving pairs of people. Journal editors and reviewers are
also recommended to know the contents of this book, because it will
likely result in new requirements for publishing dyadic research
that are essential as reliability and effect-size....[A] clear and
purposeful text for detailed how-to instructions on specific
analytical techniques....Kenny et al. make an invaluable
contribution by walking readers through ANOVA, SEM, regression, and
time-series analyses involving dyads, complete with SPSS and SAS
syntax....The book ends with an eye-opening summary of 'the seven
deadly sins of dyadic data analysis' (p. 421) that may serve as an
excellent starting point for readers with immediate analytic
concerns....Thorough, comprehensive, and clear. --Journal of
Anthropological Research, 7/30/2006Æ’Æ’ By providing readers with a
well-written, nontechnical, description of various forms of
interdependence and how they can be quantitatively analyzed, the
authors make a tremendous advancement of our field. Simply put,
this book has the potential to drastically advance the ways that
researchers conceptualize, design studies, and analyze data
involving interdependent processes....The most important
contribution of this book lies in the fact that it is the first
comprehensive treatment of how researchers can quantitatively
analyze various patterns of interdependent data....The book is
exceptionally well written. The authors have clearly made great
efforts to ensure that the book is straightforward and accessible
by writing in an extremely clear and engaging manner....I consider
this book essential reading for any psychologist who claims to have
adequate training in data analysis....Valuable reading both early
in psychologists' training, perhaps immediately after introductory
courses in multivariate statistics, and later in psychologists'
training after they have more exposure to advanced quantitative
methods....More seasoned researchers will also find this book
valuable and may even wish this book had been available earlier in
their careers....This book has the very real possibility of
sparking an important change in how researchers conceptualize,
study, and quantitatively analyze interdependent processes....I
expect that this book will have a substantial impact on the field
and highly recommend it to all psychologists who study
interdependent phenomena. --PsycCRITIQUES, 7/30/2006
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