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Dyadic Data Analysis
- Sales Rank: #770896 in Books
- Published on: 2006-07-28
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 6.25" w x 1.25" l, 1.68 pounds
- Binding: Hardcover
- 458 pages
Review
"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 2006-07-30)
"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 2006-07-30)
"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 2006-07-30)
About the Author
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.
Most helpful customer reviews
1 of 1 people found the following review helpful.
cerebellumsdayoff
By Research Reviewer
This is the bible for anyone doing dyadic research. Within the social sciences, researchers are collectively beginning to realize the importance of acknowledging interdependence in their data to conduct more meaningful statistical analyses, whether it be a simple mixed-measures ANOVA, MLM, of SEM. The authors do a fine job explaining why interdependence is important to account for and what happens if you ignore it. They follow it up with techniques of analyzing dyadic data using various statistical procedures. It helps going into this book if you are comfortable with some statistical nuts and bolts, such as the theory behind hypothesis testing and analyses of variance. Of course, knowledge of more advanced techniques such as MLM and SEM won't hurt either.
1 of 1 people found the following review helpful.
A must have for any one doing dyadic research
By Ndcas
I am using this book to assist with designing my methodology for my dissertation. The language is not technical. The authors made this text easy to understand and follow the concepts. The best thing about this text is that they start with a simple concept and build on it throughout the book so this makes it easier to learn and most importantly to retain!
2 of 2 people found the following review helpful.
A must have when you have dyads
By affinity
There are very few people who are brilliant at understanding statistics (really understanding it deeply) and gifted at explaining it to others. Kenny and his colleagues are such people. He brought us the distinction between moderators and mediators and developed the "gold standard" test for mediation. Now, he and his colleagues point out the problems inherent in analyzing dyadic data and explain how to analyze such data. If your data include 2 or more people who interact with one another, this book is a must have for data analysis.
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