This book systematically covers empirical likelihood methods in most important topics in survival analysis: the Kaplan-Meier and the Nelson-Aalen estimator, the log rank test, the Cox proportional hazards model and the accelerated failure time models. In addition, it also covers an extension of the Cox model-the short term/long term hazard ratio model of Yang and Prentice. Finally, empirical likelihood methods with current status data or type I interval censored data are investigated: estimation/test for the mean/hazard/probability and regression models are discussed. The author of this book is also the author of several R packages for empirical likelihood calculations with survival data. Every topic discussed gets immediately put into action with R code in examples that users can replicate and experiment with. Includes more than 70 examples illustrating the use of empirical likelihood, many with real data. Provides complete R computational codes that reader can replicate the results in the book. Includes over 80 exercise problems making it suitable to be adopted as a textbook.

Newly added materials now cover more general types of censored survival data. The Open Access version of this book, available atwww.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 International license.