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Autor(en) / Beteiligte
Titel
Recursive Partitioning in the Health Sciences [Elektronische Ressource]
Ist Teil von
  • Statistics for Biology and Health
Ort / Verlag
New York, NY : Springer New York
Erscheinungsjahr
1999
Link zum Volltext
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Beschreibungen/Notizen
  • Multiple complex pathways, characterized by interrelated events and conditions, 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. However, 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 demonstrate the effectiveness of a relatively recently developed methodologyrecursive partitioning-as a response to this challenge. We also compare and contrast what is learned via recursive partitioning with results obtained 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 regression techniques. This book is suitable for three broad groups of readers: (1) biomedical researchers, 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
Sprache
Englisch
Identifikatoren
ISBN: 9781475730272, 9781475730296
OCLC-Nummer: 863904719, 863904719
Titel-ID: 990018251410106463