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 …

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 …

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 …

Current status data arise when each study subject is observed only once and the survival
time of interest is known only to be either less or greater than the observation time. Such …

Current status data arise when the exact timing of an event is unobserved, and it is only
known at a given point in time whether or not the event has occurred. Recently Lin et …

In analyses of time-to-failure data with competing risks, cumulative incidence functions may
be used to estimate the time-dependent cumulative probability of failure due to specific …

In the development of many diseases there are often associated variables which
continuously measure the progress of an individual towards the final expression of the …

We extend the definition of the controlled direct effect of a point exposure on a survival
outcome, other than through some given, time-fixed intermediate variable, to the additive …

The proportional hazards model for survival time data usually assumes that the covariates of
interest take constant effects proportionally on an unspecified baseline hazard function …

We use the semiparametric accelerated failure time model to predict the survival function
and its related quantities for future subjects with a given set of covariates. We derive the …