Direction Dependence in Statistical Modeling: Methods of Analysis
暫譯: 統計建模中的方向依賴性：分析方法

Wiedermann, Wolfgang, Kim, Daeyoung, Sungur, Engin A.

Direction Dependence in Statistical Modeling: Methods of Analysis
  • 出版商: Wiley
  • 出版日期: 2020-12-03
  • 售價: $4,760
  • 貴賓價: 9.5 折 $4,522
  • 語言: 英文
  • 頁數: 432
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1119523079
  • ISBN-13: 9781119523079

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

本書編輯探討了與方向依賴相容的假設統計分析的當前方法。該書分為四個部分，每個部分包含兩章或更多章，共計14章。本書的第一部分介紹了統計模型中方向依賴的基本概念。作者提供了關於回歸線中依賴方向研究起源的歷史觀點。介紹了具有方向依賴性質的各類聯合分布（copulas）。此外，還對聯合回歸函數和方向依賴建模中的順序統計量的伴隨變量進行了介紹。提議書的第二部分專注於連續變量的方向依賴建模的最新發展和進展，包含六章。作者展示了將方向依賴概念納入以識別因果模型的好處。提議書的第三部分介紹了類別變量情況下的方向依賴方法。最後，提議書的第四部分專注於實質理論和現實世界應用，包含四章。作者在SPSS中介紹了自定義對話框和宏，以使方向依賴分析對應用實證研究者更為可及。

作者簡介

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.

作者簡介(中文翻譯)

**沃爾夫岡·維德曼（WOLFGANG WIEDERMANN）**是密蘇里大學哥倫比亞分校的副教授。他在奧地利克拉根福大學獲得量化心理學的博士學位。他的主要研究興趣包括因果推斷方法的發展、確定觀察數據中依賴關係的因果方向的方法，以及針對個人導向研究環境的方法。他編輯了有關因果推斷的統計方法進展的書籍（與von Eye合編，Wiley）以及社會和行為科學中依賴數據分析的統計方法新發展的書籍（與Stemmler和von Eye合編）。

**金大勇（DAEYOUNG KIM）**是馬薩諸塞州大學阿默斯特分校的數學與統計副教授。他在賓夕法尼亞州立大學獲得統計學的博士學位。他的原始研究興趣集中在有限混合模型中的似然推斷，包括經驗可識別性和多模態性，發展幾何和計算方法以劃定多維推斷函數，以及在不完全觀察的類別數據中的似然推斷，隨後專注於使用（子）copula回歸分析多變量數據中的非對稱關聯。

**恩金·A·桑古爾（ENGIN A. SUNGUR）**擁有城市與區域規劃的學士學位（中東技術大學，METU，土耳其）、應用統計的碩士學位（METU）、統計學的碩士學位（卡內基梅隆大學，CMU）和統計學的博士學位（CMU）。他曾在卡內基梅隆大學、匹茲堡大學、中東技術大學和愛荷華大學任教。目前，他是明尼蘇達大學莫里斯分校的摩爾斯校友傑出統計學教授。他教授統計學已超過38年，其中29年在明尼蘇達大學莫里斯分校。他的研究領域包括依賴建模，重點是方向依賴、現代多變量統計、極值理論和統計教育。

**亞歷山大·馮·艾（ALEXANDER VON EYE）**是密歇根州立大學（MSU）心理學的名譽教授。他在德國特里爾大學獲得心理學的博士學位。他獲得了美國統計協會（American Statistical Association）頒發的專業統計師認證（PSTATTM）。他的研究重點包括（1）開發和測試用於分析類別和縱向數據的統計方法，以及分析方向依賴假設的統計方法。此外（2），他是MSU的一個研究團隊成員（與Bogat、Levendosky和Lonstein合作），該團隊研究暴力對女性及其新生兒的影響。他的第三個研究興趣（3）涉及在實證研究中個人導向的理論發展和應用分析。

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