Recursive Partitioning in the Health Sciences
Authors: Zhang, Heping, Singer, Burton
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- About this book
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Multiple complex pathways, characterized by interrelated events and con ditions, represent routes to many illnesses, diseases, and ultimately death. Although there are substantial data and plausibility arguments supporting many conditions as contributory components of pathways to illness and disease end points, we have, historically, lacked an effective methodology for identifying the structure of the full pathways. Regression methods, with strong linearity assumptions and data-based constraints on the extent and order of interaction terms, have traditionally been the strategies of choice for relating outcomes to potentially complex explanatory pathways. How ever, nonlinear relationships among candidate explanatory variables are a generic feature that must be dealt with in any characterization of how health outcomes come about. Thus, the purpose of this book is to demon strate the effectiveness of a relatively recently developed methodology recursive partitioning-as a response to this challenge. We also compare and contrast what is learned via recursive partitioning with results ob tained on the same data sets using more traditional methods. This serves to highlight exactly where--and for what kinds of questions-recursive partitioning-based strategies have a decisive advantage over classical re gression techniques. This book is suitable for three broad groups of readers: (1) biomedical re searchers, clinicians, public health practitioners including epidemiologists, health service researchers, environmental policy advisers; (2) consulting statisticians who can use the recursive partitioning technique as a guide in providing effective and insightful solutions to clients' problems; and (3) statisticians interested in methodological and theoretical issues.
- Reviews
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STATISTICAL METHODS IN MEDICAL RESEARCH
"The beauty of the Zhang and Singer’s book is that it gives an excellent comparison between conventional regression models and recursive partitioning techniques. This comparative approach gives the reader insight into how a recursive partitioning technique can have an advantage over the conventional methods…Overall, the book provides an excellent introduction to tree based methods and their applications. It can be a good place to start learning about recursive partitioning. In addition, biostatisticians will enjoy the real life examples that have been used in the book."
- Table of contents (12 chapters)
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Introduction
Pages 1-6
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A Practical Guide to Tree Construction
Pages 7-19
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Logistic Regression
Pages 21-27
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Classification Trees for a Binary Response
Pages 29-59
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Risk-Factor Analysis Using Tree-Based Stratification
Pages 61-69
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Table of contents (12 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Recursive Partitioning in the Health Sciences
- Authors
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- Heping Zhang
- Burton Singer
- Series Title
- Statistics for Biology and Health
- Copyright
- 1999
- Publisher
- Springer-Verlag New York
- Copyright Holder
- Springer Science+Business Media New York
- eBook ISBN
- 978-1-4757-3027-2
- DOI
- 10.1007/978-1-4757-3027-2
- Series ISSN
- 1431-8776
- Edition Number
- 1
- Number of Pages
- XII, 226
- Number of Illustrations
- 47 b/w illustrations
- Topics
