| 书目名称 | Recursive Partitioning in the Health Sciences | | 编辑 | Heping Zhang,Burton Singer | | 视频video | | | 丛书名称 | Statistics for Biology and Health | | 图书封面 |  | | 描述 | 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 wh | | 出版日期 | Book 19991st edition | | 关键词 | Computerassistierte Detektion; Factor analysis; Logistic Regression; Radiologieinformationssystem; Recur | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-3027-2 | | isbn_ebook | 978-1-4757-3027-2Series ISSN 1431-8776 Series E-ISSN 2197-5671 | | issn_series | 1431-8776 | | copyright | Springer Science+Business Media New York 1999 |
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发表于 2025-3-21 17:13:55
