Direction Dependence Analysis
Foundations and Statistical Methods
Published on 14. August 2025
Book
Paperback/Softback
388 pages
978-1-009-38139-0 (ISBN)
Description
While regression analysis is widely understood, it falls short in determining the causal direction of relationships in observational data. In this groundbreaking volume, Wiedermann and von Eye introduce Direction Dependence Analysis (DDA), a novel method that leverages variable information often overlooked by traditional techniques, such as higher-order moments like skewness and kurtosis. DDA reveals the asymmetry properties of regression and correlation, enabling researchers to evaluate competing causal hypotheses, assess the roles of variables in causal flows, and develop statistical methods for testing causal direction. This book provides a comprehensive formal description of DDA, illustrated with both artificial and real-world data examples. Additionally, readers will find free software implementations of DDA, making this an essential resource for researchers seeking to enhance their understanding of causal relationships in data analysis.
Reviews / Votes
'Will we ever find out which of the chicken or the egg came first? The answer may lie beyond the Gaussian world. This is the fascinating premise of this unique book, which distills 25 years of intensive research into the groundbreaking field of directional dependence analysis.' Yadolah Dodge, Professor Emeritus, University of Neuchatel, and Valentin Rousson, Associate Professor, University of Lausanne 'Wiedermann and von Eye provide a singularly erudite, integrative, comprehensive, and accessible roadmap for using direction dependence analysis to illuminate new and greatly needed methodological advances for establishing causality in real-word data. Across psychological science and other disciplines, researchers will find that this book presents powerful and creative means to rigorously identify causal relations in both basic and applied research.' Richard M. Lerner, Bergstrom Chair in Applied Developmental Science and Director, Institute for Applied Research in Youth Development, Tufts University 'Wiedermann and von Eye's new book describes a refreshingly new approach to causal inference based on directional dependence. The new method provides information other than theory and prior empirical work by which to assess the causal dependence between variables. It is the first comprehensive book on this new method and provides a well-organized and clearly written account of this unique method, with plenty of examples.' David P. MacKinnon, Foundation and Regents Professor, Department of Psychology, Arizona State University 'Correlation is not causality! Does X cause Y, or Y cause X? Because correlations are symmetric for X and Y, we can't know... Until now! I first encountered Direction Dependence Analysis (DDA) in a paper by this book's authors. DDA is a brilliant idea: Use higher order moments to inform directionality. My thinking about correlations immediately became more nuanced and exciting. Read this book, and yours will too.' Joe Rodgers, Professor Emeritus of Psychology and Human Development, Vanderbilt UniversityMore details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
College/higher education
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 21 mm
Weight
561 gr
ISBN-13
978-1-009-38139-0 (9781009381390)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Wolfgang Wiedermann | Alexander von Eye
Direction Dependence Analysis
Foundations and Statistical Methods
Book
08/2025
Cambridge University Press
€124.20
Shipment within 15-20 days
Persons
Wolfgang Wiedermann is Professor of Statistics, Measurement, and Evaluation in Education in the College of Education and Human Development at the University of Missouri, Columbia. He received his Ph.D. in Quantitative Psychology from the University of Klagenfurt, Austria. His work focuses on the development of methods for causal structure learning and causal inference, distributional regression, and methods for person-oriented research. He has co-authored books on the general linear model (in 2023) and Configural Frequency Analysis (in 2021) and edited volumes on direction dependence modeling (in 2020) and statistics and causality (in 2016). His work appears in journals such as Psychological Methods, Multivariate Behavioral Research, Behavior Research Methods, Prevention Science, Developmental Psychology, and Development and Psychopathology. Alexander von Eye, is Professor Emeritus of Psychology at Michigan State University. He received his Ph.D. in Psychology from the University of Trier, Germany, in 1976. His work focuses on categorical data analysis, methods of analysis of direction dependence hypotheses, person-oriented research, and human development. He authored texts on, e.g., Configural Frequency Analysis (with Wiedermann), and on log-linear modeling, and he edited, e.g., a book on statistics and causality (with Wiedermann). His over 400 articles appeared in the premier journals of the field, including Psychological Methods, Multivariate Behavioral Research, Child Development, the American Statistician, and the Journal of Applied Statistics.
Content
1. Introduction; 2. The linear regression model; 3. Asymmetry properties of distributions of observed variables; 4. Asymmetry properties of error distributions; 5. Independence properties of causes and errors; 6. Direction of dependence under latent confounding; 7. The integrated framework of Direction Dependence Analysis; 8. Stability and sensitivity analyses; 9. Extensions and applications; 10. Statistical software; 11. Concluding remarks.