The efficacy of an HIV vaccine to prevent infection is likely to depend on the genetic variation
of the exposing virus. This paper addresses the problem of using data on the HIV sequences …

Typically, differences in the effect of treatment on competing risks are compared by a
weighted log-rank test. This test compares the cause specific hazard rates between the …

It is of interest in some applications to determine whether there is a relationship between a
hazard rate function (or a cumulative incidence function) and a mark variable which is only …

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 …

This article develops omnibus tests for comparing cause‐specific hazard rates and
cumulative incidence functions at specified covariate levels. Confidence bands for the …

The cumulative incidence function quantifies the probability of failure over time due to a
specific cause for competing risks data. The generalized semiparametric regression models …

In the evaluation of efficacy of a vaccine to protect against disease caused by a genetically
diverse infectious pathogen, it is often important to assess whether vaccine protection …

An empirical likelihood based test for comparing the incidence functions for multiple
competing risks is proposed, without making any assumptions on the distribution of the …

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 …

The authors study the problem of checking the adequacy of a parametric model for a
distribution using several possibly censored weight biased samples. They discuss …