| 书目名称 | Dynamic Regression Models for Survival Data |
| 编辑 | Torben Martinussen,Thomas H. Scheike |
| 视频video | |
| 概述 | A key issue in this book is extensions of the Cox model and alternative models with most of them having the specific aim to be able to deal with time-varying effects of covariates in regression analys |
| 丛书名称 | Statistics for Biology and Health |
| 图书封面 |  |
| 描述 | .In survival analysis there has long been a need for models that goes beyond the Cox model as the proportional hazards assumption often fails in practice. This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the specific aim of describing time-varying effects of explanatory variables. One model that receives special attention is Aalen’s additive hazards model that is particularly well suited for dealing with time-varying effects. The book covers the use of residuals and resampling techniques to assess the fit of the models and also points out how the suggested models can be utilised for clustered survival data. The authors demonstrate the practically important aspect of how to do hypothesis testing of time-varying effects making backwards model selection strategies possible for the flexible models considered...The use of the suggested models and methods is illustrated on real data examples. The methods are available in the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets. This gives the reader a unique ch |
| 出版日期 | Book 2006 |
| 关键词 | Counting; Resampling; Statistica; cluster; counting process; permutation tests; point process; selection; se |
| 版次 | 1 |
| doi | https://doi.org/10.1007/0-387-33960-4 |
| isbn_softcover | 978-1-4419-1904-5 |
| isbn_ebook | 978-0-387-33960-3Series ISSN 1431-8776 Series E-ISSN 2197-5671 |
| issn_series | 1431-8776 |
| copyright | Springer-Verlag New York 2006 |
发表于 2025-3-21 19:46:33
