| 書(shū)目名稱(chēng) | Recursive Partitioning in the Health Sciences | | 編輯 | Heping Zhang,Burton Singer | | 視頻video | http://file.papertrans.cn/825/824360/824360.mp4 | | 叢書(shū)名稱(chēng) | Statistics for Biology and Health | | 圖書(shū)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 | | 關(guān)鍵詞 | 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 |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國(guó)際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-14 12:51
發(fā)表于 2025-3-21 17:13:55
