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"Discover the groundbreaking Direction Dependence Analysis (DDA), a powerful statistical method that enhances traditional regression and structural modeling by evaluating causal direction between variables. This book offers formal DDA methodologies, real-world applications, and introduces userfriendly DDA software for effective data analysis"--
List of contents
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.
About the author
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.
Summary
Discover the groundbreaking Direction Dependence Analysis (DDA), a powerful statistical method that enhances traditional regression and structural modeling by evaluating causal direction between variables. This book offers formal DDA methodologies, real-world applications, and introduces user-friendly DDA software for effective data analysis.
Foreword
Direction Dependence Analysis offers a coherent method to derive and test hypotheses about causal relationships and their directional effects.
