Modelling survival data in medical research
Author(s)
Bibliographic Information
Modelling survival data in medical research
（Texts in statistical science）
CRC Press, an imprint of the Taylor & Francis Group, 2023
4th ed.
- : hardback
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Note
Includes bibliographical references (p. 507-527) and index.
Description and Table of Contents
Description
Hugely popular textbook on survival analysis for graduate students of statistics and biostatistics, mainly due to its accessibility and breadth of examples.
This is a standard course on graduate programs in biostatistics and statistics, and this is one of the most popular textbooks.
Updated with modern methods covering Bayesian survival analysis, joint models, and more.
Table of Contents
1. Survival analysis 2. Some non-parametric procedures 3. The Cox regression model 4. Model checking in the Cox regression model 5. Parametric regression models 6. Flexible parametric models 7. Model checking in parametric models 8. Time-dependent variables 9. Interval-censored survival data 10. Frailty models 11. Non-proportional hazards and institutional comparisons 12 Competing risks 13. Multiple events and event history modelling 14. Dependent censoring 15. Sample size requirements for a survival study 16. Bayesian survival analysis 17. Survival Analysis with R
by "Nielsen BookData"