Add the Empirical Likelihood to Your Nonparametric Toolbox
Empirical Likelihood Method in Survival Analysis explains how to
use the empirical likelihood method for right censored survival
data. The author uses R for calculating empirical likelihood and
includes many worked out examples with the associated R code. The
datasets and code are available for download on his website and
CRAN. The book focuses on all the standard survival analysis topics
treated with empirical likelihood, including hazard functions,
cumulative distribution functions, analysis of the Cox model, and
computation of empirical likelihood for censored data. It also
covers semi-parametric accelerated failure time models, the
optimality of confidence regions derived from empirical likelihood
or plug-in empirical likelihood ratio tests, and several empirical
likelihood confidence band results. While survival analysis is a
classic area of statistical study, the empirical likelihood
methodology has only recently been developed. Until now, just one
book was available on empirical likelihood and most statistical
software did not include empirical likelihood procedures.
Addressing this shortfall, this book provides the functions to
calculate the empirical likelihood ratio in survival analysis as
well as functions related to the empirical likelihood analysis of
the Cox regression model and other hazard regression models.
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