When analyzing time-to-event data, it often happens that a certain fraction of the data
corresponds to subjects who will never experience the event of interest. These event times …

A semiparametric model for observational data combines a parametric form for some
component of the data generating process (usually the behavioral relation between the …

Data-analytic approaches to regression problems, arising from many scientific disciplines
are described in this book. The aim of these nonparametric methods is to relax assumptions …

For the past two decades the Cox proportional hazards model has been used extensively to
examine the covariate effects on the hazard function for the failure time variable. On the …

Semiparametric models are those where the functional form of some components is
unknown. Efficiency bounds are of fundamental importance for such models. They provide a …

A class of tests and estimators for the parameters of the Cox proportional hazards model, the
accelerated failure time model, and a model for the effect of treatment on the mean of a …

This volume examines modern techniques and research problems in the analysis of lifetime
data analysis. This area of statistics deals with time-to-event data which is complicated not …

A class of estimates for regression parameters in a linear model with right censored data is
proposed. These estimates are derived by using linear rank tests for right censored data as …

We argue, that due to the curse of dimensionality, there are major difficulties with any pure or
smoothed likelihood‐based method of inference in designed studies with randomly missing …

A broad class of rank‐based monotone estimating functions is developed for the
semiparametric accelerated failure time model with censored observations. The …