Competing risk analysis is commonly applied to time-to-event data with finitely many causes
of failure. It alters the probability of the occurrence of an event of interest broken down by a …

For time-to-event data with finitely many competing risks, the proportional hazards model
has been a popular tool for relating the cause-specific outcomes to covariates (. The …

For time-to-event data with finitely many competing risks, the proportional hazards model
has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al …

An objective of randomized placebo-controlled preventive HIV vaccine efficacy (VE) trials is
to assess the relationship between vaccine effects to prevent HIV acquisition and continuous …

For survival data, mark variables are only observed at uncensored failure times, and it is of
interest to investigate whether there is any relationship between the failure time and the …

In randomized placebo-controlled preventive HIV vaccine efficacy trials, an objective is to
evaluate the relationship between vaccine efficacy to prevent infection and genetic …

Motivated by the need to assess HIV vaccine efficacy, previous studies proposed an
extension of the discrete competing risks proportional hazards model, in which the cause of …

Competing risks occur in a time-to-event analysis in which a patient can experience one of
several types of events. Traditional methods for handling competing risks data presuppose …

Methods for Comparing Mark-specific Hazards and Cumulative Incidence Functions
Between Two Groups, with Application to HIV Vacci Page 1 Methods for Comparing Mark-specific …

In the past decade, several principal stratification–based statistical methods have been
developed for testing and estimation of a treatment effect on an outcome measured after a …