The additive hazards model specifies that the hazard function conditional on a set of
covariates is the sum of an arbitrary baseline hazard function and a regression function of …

The additive hazards regression model relates the conditional hazard function of the failure
time linearly to the covariates. This formulation complements the familiar proportional …

In contrast to the proportional hazards model, the additive risk model specifies that the
hazard function associated with a set of possibly time-varying covariates is the sum of, rather …

Current status data arise when the only knowledge about the failure time of interest is
whether the failure occurs before or after a random monitoring time. We propose to analyse …

One method for estimating the hazard function is to use a parametric estimator, provided that
the underlying distribution of the data can be assumed to belong to some well known family …

We consider the additive hazard model when some of the true covariates are measured only
on a randomly selected validation set whereas auxiliary covariates are observed for all study …

The additive risk model assumes that the hazard function associated with a set of covariates
is the sum of the baseline hazard function and the regression function of covariates. We …

In this article, the authors consider a semiparametric additive hazards regression model for
right‐censored data that allows some censoring indicators to be missing at random. They …

In this article we study estimation in the additive hazards regression model with missing
censoring indicators. We develop simple procedures to obtain consistent and efficient …

Marginal additive hazards models are considered for multivariate survival data in which
individuals may experience events of several types and there may also be correlation …