The authors of this monograph have developed a large and important class of survival
analysis models that generalize most of the existing models. In a unified, systematic …

The field of survival analysis emerged in the 20th century and experienced tremendous
growth during the latter half of the century. The developments in this field that have had the …

In this paper we consider a class of semi-parametric transformation models, under which an
unknown transformation of the survival time is linearly related to the covariates with various …

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 …

Semiparametric regression models play a central role in formulating the effects of covariates
on potentially censored failure times and in the joint modelling of incomplete repeated …

In medical studies, time-to-event outcomes such as time to death or relapse of a disease are
routinely recorded along with longitudinal data that are observed intermittently during the …

OBJECTIVE: To compare and evaluate ranking, regression and combined machine learning
approaches for the analysis of survival data. METHODS: The literature describes two …

A class of semiparametric transformation models is proposed to characterise the effects of
possibly time-varying covariates on the intensity functions of counting processes. The class …

Regression models for survival data are often specified from the hazard function while
classical regression analysis of quantitative outcomes focuses on the mean value (possibly …

Longitudinal studies often incur several problems that challenge standard statistical
methods for data analysis. These problems include non-ignorable missing data in …