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Full Description
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.
Mai Zhou is a professor emeritus at University of Kentucky. He received his Ph.D. degree in Statistics from Columbia University.
Contents
Preface to First Edition Preface to Second Edition Author 1 Introduction 2 Empirical Likelihood for Linear Functionals of Hazard 3 Empirical Likelihood for Linear Functionals of Cumulative Distribution Function 4 Empirical Likelihood Analysis of the Cox Model 5 Empirical Likelihood Analysis of Accelerated Failure Time Models 6 Computation of Empirical Likelihood Ratio with Right Cen-sored Data 7 Empirical Likelihood: Some Applications 8 Optimality of Empirical Likelihood for Right Censored Data 9 Miscellaneous 10 Empirical Likelihood for Two Independent Samples 11 Current Status Data Bibliography Index
