Fan et al. are to be congratulated for this important contribution to the analysis of multivariate
failure time data. They have provided three regression parameter estimators for multiple …

Multivariate failure time data arise frequently in survival analysis. A commonly used
technique is the working independence estimator for marginal hazard models. Two natural …

The choice of weights in estimating equations for multivariate survival data is considered.
Specifically, we consider families of weight functions which are constant on fixed time …

Many survival studies record the times to two or more distinct failures on each subject. The
failures may be events of different natures or may be repetitions of the same kind of event. In …

This dissertation proposes variable selection methods for reducing dimensionality in
complex lifetime data for survival analysis. With the advent of big data, survival analysis …

Variable selection is fundamental in high-dimensional statistical modeling. Many authors
have proposed various variable selection criteria and procedures for linear regression …

Survival analysis is absorbed to analysis of time to event data. To handle these outcomes,
as well as censored observations, where the event was not observed during follow-up …

There is no doubt that this book is an important contribution to the literature of multivariate
survival analysis. Unlike other books on survival, most of which have just one or two …

SYNOPTIC ABSTRACT Much research has been conducted over the last thirty years in
developing and characterizing multivariate survival distributions. Typically, the multivariate …

Incomplete covariate data is a common occurrence in many studies in which the outcome is
survival time. With generalized linear models, when the missing covariates are categorical, a …