Kowalski / Tu Modern Applied U-Statistics

1. Auflage 2008
ISBN: 978-0-470-18645-9
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 400 Seiten, E-Book

Reihe: Wiley Series in Probability and Statistics

A timely and applied approach to the newly discovered methods andapplications of U-statistics
Built on years of collaborative research and academic experience,Modern Applied U-Statistics successfully presents a thoroughintroduction to the theory of U-statistics using in-depth examplesand applications that address contemporary areas of study includingbiomedical and psychosocial research. Utilizing a "learn byexample" approach, this book provides an accessible, yet in-depth,treatment of U-statistics, as well as addresses key concepts inasymptotic theory by integrating translational andcross-disciplinary research.
The authors begin with an introduction of the essential andtheoretical foundations of U-statistics such as the notion ofconvergence in probability and distribution, basic convergenceresults, stochastic Os, inference theory, generalized estimatingequations, as well as the definition and asymptotic properties ofU-statistics. With an emphasis on nonparametric applications whenand where applicable, the authors then build upon this establishedfoundation in order to equip readers with the knowledge needed tounderstand the modern-day extensions of U-statistics that areexplored in subsequent chapters. Additional topical coverageincludes:
Longitudinal data modeling with missing data
Parametric and distribution-free mixed-effect and structuralequation models
A new multi-response based regression framework for non-parametricstatistics such as the product moment correlation, Kendall's tau,and Mann-Whitney-Wilcoxon rank tests
A new class of U-statistic-based estimating equations (UBEE) fordependent responses
Motivating examples, in-depth illustrations of statistical andmodel-building concepts, and an extensive discussion oflongitudinal study designs strengthen the real-world utility andcomprehension of this book. An accompanying Web site features SAS?and S-Plus? program codes, software applications, and additionalstudy data. Modern Applied U-Statistics accommodates second- andthird-year students of biostatistics at the graduate level and alsoserves as an excellent self-study for practitioners in the fieldsof bioinformatics and psychosocial research.

Autoren/Hrsg.

Kowalski, Jeanne

Tu, Xin M.

Inhaltsverzeichnis

Preface.
1. Preliminaries.
2. Models for Cross-Sectional Data.
3. Univariate U-Statistics.
4. Models for Clustered Data.
5. Multivariate U-Statistics.
6. Functional response Models.
References.
Subject Index.

Über Autor(innen)

Jeanne Kowalski, PhD, is Assistant Professor in the Division ofOncology Biostatistics at The Johns Hopkins University. Dr.Kowalski has authored or coauthored over thirty journal articlesthat focus on a wide range of issues in medicine and public healththrough the use of novel statistical methods, includingU-statistics, generalized linear mixed-effects models, generalizedestimating equations, asymptotics, and measurement errormodels.
Xin M. Tu, PhD, is Professor in the Department of Biostatisticsand Computational Biology as well as the Department of Psychiatryat The University of Rochester in New York. Dr. Tu has authored orcoauthored over ninety publications in peer-reviewed journalsduring his career and is acclaimed as one of the best-versedauthorities in the area of U-statistics.