Direction Dependence in Statistical Modeling : Methods of Analysis

Wiedermann, Wolfgang (EDT); Kim, Daeyoung (EDT); Sungur, Engin A. (EDT); Von Eye, Alexander (EDT)

ISBN 10: 1119523079 / ISBN 13: 9781119523079

Edité par Wiley, 2020

A propos de cet article

N° de réf. du vendeur 33753445-n

Détails bibliographiques

• Titre: Direction Dependence in Statistical Modeling : Methods of Analysis
• Éditeur: Wiley
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 1119523079
• ISBN à 13 chiffres: 9781119523079
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

"This edited book examines current methods for the statistical analysis of hypotheses that are compatible with direction dependence. The proposed book is divided in four parts, each consisting of two or more chapters, for a total of 14 chapters. The first part of this book introduces the fundamental concepts of direction dependence in statistical models. The authors provide a historical view on the origins of studying the direction of dependence in a regression line. Various classes of copulas with directional dependence properties are introduced. In addition, an introduction into copula regression functions and concomitants of order statistics in directional dependence modeling is given. Part II of the proposed book is devoted to recent developments and advances in direction dependence modeling of continuous variables and contains six chapters. The author demonstrates the benefits of incorporating concepts of direction dependence to identify causal models. Part III of the proposed volume introduces direction dependence methods for the categorical variable case. Finally, Part IV of the proposed book is devoted to substantive theory and real-world applications and consists of four chapters. The author introduces custom dialogs and macros in SPSS to make direction dependence analysis accessible to applied empirical researchers."--

À propos de l?auteur

WOLFGANG WIEDERMANN is Associate Professor at the University of Missouri-Columbia. He received his Ph.D. in Quantitative Psychology from the University of Klagenfurt, Austria. His primary research interests include the development of methods for causal inference, methods to determine the causal direction of dependence in observational data, and methods for person-oriented research settings. He has edited books on advances in statistical methods for causal inference (with von Eye, Wiley) and new developments in statistical methods for dependent data analysis in the social and behavioral sciences (with Stemmler and von Eye).

DAEYOUNG KIM is Associate Professor of Mathematics and Statistics at the University of Massachusetts, Amherst. He received his Ph.D. from the Pennsylvania State University in Statistics. His original research interests were in likelihood inference in finite mixture modelling including empirical identifiability and multimodality, development of geometric and computational methods to delineate multidimensional inference functions, and likelihood inference in incompletely observed categorical data, followed by a focus on the analysis of asymmetric association in multivariate data using (sub)copula regression.

ENGIN A. SUNGUR has a B.A. in City and Regional Planning (Middle East Technical University, METU, Turkey), M.S. in Applied Statistics, METU, M.S. in Statistics (Carnegie-Mellon University, CMU) and Ph.D. in Statistics (CMU). He taught at Carnegie-Mellon University, University of Pittsburg, Middle East Technical University, and University of Iowa. Currently, he is a Morse-Alumni distinguished professor of statistics at University of Minnesota Morris. He is teaching statistics for more than 38 years, 29 years of which is at the University of Minnesota Morris. His research areas are dependence modeling with emphasis on directional dependence, modern multivariate statistics, extreme value theory, and statistical education.

ALEXANDER VON EYE is Professor Emeritus of Psychology at Michigan State University (MSU). He received his Ph.D. in Psychology from the University of Trier, Germany. He received his accreditation as Professional Statistician from the American Statistical Association (PSTATTM). His research focuses (1) on the development and testing of statistical methods for the analysis of categorical and longitudinal data, and for the analysis of direction dependence hypotheses. In addition (2), he is member of a research team at MSU (with Bogat, Levendosky, and Lonstein) that investigates the effects of violence on women and their newborn children. His third area of interest (3) concerns theoretical developments and applied analysis of person-orientation in empirical research.