Direction Dependence in Statistical Modeling
eBook - PDF

Direction Dependence in Statistical Modeling

Methods of Analysis

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Direction Dependence in Statistical Modeling

Methods of Analysis

About this book

Covers the latest developments in direction dependence research

Direction Dependence in Statistical Modeling: Methods of Analysis incorporates the latest research for the statistical analysis of hypotheses that are compatible with the causal direction of dependence of variable relations. Having particular application in the fields of neuroscience, clinical psychology, developmental psychology, educational psychology, and epidemiology, direction dependence methods have attracted growing attention due to their potential to help decide which of two competing statistical models is more likely to reflect the correct causal flow.

The book covers several topics in-depth, including:

  • A demonstration of the importance of methods for the analysis of direction dependence hypotheses
  • A presentation of the development of methods for direction dependence analysis together with recent novel, unpublished software implementations
  • A review of methods of direction dependence following the copula-based tradition of Sungur and Kim
  • A presentation of extensions of direction dependence methods to the domain of categorical data
  • An overview of algorithms for causal structure learning

The book's fourteen chapters include a discussion of the use of custom dialogs and macros in SPSS to make direction dependence analysis accessible to empirical researchers.

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Yes, you can access Direction Dependence in Statistical Modeling by Wolfgang Wiedermann, Daeyoung Kim, Engin A. Sungur, Alexander von Eye, Wolfgang Wiedermann,Daeyoung Kim,Engin A. Sungur,Alexander von Eye in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2020
Print ISBN
9781119523079
eBook ISBN
9781119523130
Edition
1
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Contents
  5. About the Editors
  6. Notes on Contributors
  7. Acknowledgments
  8. Preface
  9. Part I Fundamental Concepts of Direction Dependence
  10. Chapter 1 From Correlation to Direction Dependence Analysis 1888ā€“2018
  11. Chapter 2 Direction Dependence Analysis: Statistical Foundations and Applications
  12. Chapter 3 The Use of Copulas for Directional Dependence Modeling
  13. Part II Direction Dependence in Continuous Variables
  14. Chapter 4 Asymmetry Properties of the Partial Correlation Coefficient: Foundations for Covariate Adjustment in Distributionā€Based Direction Dependence Analysis
  15. Chapter 5 Recent Advances in Semiā€Parametric Methods for Causal Discovery
  16. Chapter 6 Assumption Checking for Directional Causality Analyses
  17. Chapter 7 Complete Dependence: A Survey
  18. Part III Direction Dependence in Categorical Variables
  19. Chapter 8 Locating Direction Dependence Using Logā€Linear Modeling, Configural Frequency Analysis, and Prediction Analysis
  20. Chapter 9 Recent Developments on Asymmetric Association Measures for Contingency Tables
  21. Chapter 10 Analysis of Asymmetric Dependence for Threeā€Way Contingency Tables Using the Subcopula Approach
  22. Part IV Applications and Software
  23. Chapter 11 Distributionā€Based Causal Inference: A Review and Practical Guidance for Epidemiologists
  24. Chapter 12 Determining Causality in Relation to Early Risk Factors for ADHD: The Case of Breastfeeding Duration
  25. Chapter 13 Direction of Effect Between Intimate Partner Violence and Mood Lability: A Granger Causality Model
  26. Chapter 14 On the Causal Relation of Academic Achievement and Intrinsic Motivation: An Application of Direction Dependence Analysis Using SPSS Custom Dialogs
  27. Author Index
  28. Subject Index
  29. EULA