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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.
'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 Neuchâtel, 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 University
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