Bootstrap Methods: A Guide for Practitioners and Researchers (Wiley Series in Probability and Statistics) - Hardcover

Über die Autorin bzw. den Autor

Michael R. Chernick, PhD, is Principal Senior Statistician at United BioSource Corporation, providing statistical design and analysis for pharmaceutical research on a variety of diseases, including a recent emphasis on oncology. He has over twenty years of experience in the application of statistical methods to the pharmaceutical industry as well as to medical devices, energy data, engineering problems, and insurance data. His research interests include extreme value theory, outliers, data editing, time series, and bootstrap methods. Dr. Chernick is also the coauthor of Introductory Biostatistics for the Health Sciences (Wiley).

Von der hinteren Coverseite

A practical and accessible introduction to the bootstrap method――newly revised and updated

Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics.

Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features:

• The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field

• A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials

• A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks

• Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data

• New examples and illustrations as well as extensive historical notes at the end of each chapter

With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.

Aus dem Klappentext

A practical and accessible introduction to the bootstrap method--newly revised and updated
 
Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics.
 
Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features:
*
 
The addition of a second, extended bibliography devoted solely to publications from 1999-2007, which is a valuable collection of references on the latest research in the field
*
 
A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials
*
 
A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks
*
 
Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data
*
 
New examples and illustrations as well as extensive historical notes at the end of each chapter
 
With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.