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Kernel regression for cause-specific hazard models with time-dependent coefficients
Competing risk data appear widely in modern biomedical research. In the past two decades, cause-specific hazard models are often used to deal with...
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Scalable proximal methods for cause-specific hazard modeling with time-varying coefficients
Survival modeling with time-varying coefficients has proven useful in analyzing time-to-event data with one or more distinct failure types. When...
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Analysis of the time-varying Cox model for the cause-specific hazard functions with missing causes
This paper studies the Cox model with time-varying coefficients for cause-specific hazard functions when the causes of failure are subject to...
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The built-in selection bias of hazard ratios formalized using structural causal models
It is known that the hazard ratio lacks a useful causal interpretation. Even for data from a randomized controlled trial, the hazard ratio suffers...
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Asymptotic justification of maximum likelihood estimation for the proportional excess hazard model in analysis of cancer registry data
Population-based cancer registry studies are conducted to investigate the various cancer question and have important impacts on cancer control. In...
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Multiple imputation with competing risk outcomes
In time-to-event analyses, a competing risk is an event whose occurrence precludes the occurrence of the event of interest. Settings with competing...
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A general multivariate lifetime model with a multivariate additive process as conditional hazard rate increment process
The object of the present paper is the study of the joint lifetime of d components subject to a common stressful external environment. Out of the...
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Bayesian Modeling of Survival Data in the Presence of Competing Risks with Cure Fractions and Masked Causes
In handling the presence of multiple competing risks, methods such as the multivariate failure times model, mixture model, subdistribution model...
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Non-parametric test of recurrent cumulative incidence functions for competing risks models
Recurrent competing risks data are common in survival studies. In such contexts the effects of competing risks on lifetime outcomes are important...
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Longitudinal mediation analysis of time-to-event endpoints in the presence of competing risks
This proposal is motivated by an analysis of the English Longitudinal Study of Ageing (ELSA), which aims to investigate the role of loneliness in...
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Subtleties in the interpretation of hazard contrasts
The hazard ratio is one of the most commonly reported measures of treatment effect in randomised trials, yet the source of much misinterpretation....
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Investigating non-inferiority or equivalence in time-to-event data under non-proportional hazards
The classical approach to analyze time-to-event data, e.g. in clinical trials, is to fit Kaplan–Meier curves yielding the treatment effect as the...
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Inferences on cumulative incidence function for middle censored survival data with Weibull regression
This article considers the problem of competing risks analysis in the presence of middle censoring scheme. In this censoring, the exact lifetime of...
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Magnitude Orders
A stochastic order is a partial order that quantifies the concept of one random variable being bigger than (or more variable or more skewed) another...
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Semiparametric regression analysis of window-observation recurrent event data with multiple causes of failure
This article deals with the regression analysis of recurrent event data with multiple causes of failure that are collected in disconnected...
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Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring
We consider a novel class of semiparametric joint models for multivariate longitudinal and survival data with dependent censoring. In these models,...
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Semiparametric regression and risk prediction with competing risks data under missing cause of failure
The cause of failure in cohort studies that involve competing risks is frequently incompletely observed. To address this, several methods have been...
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Competing risks regression with dependent multiple spells: Monte Carlo evidence and an application to maternity leave
Copulas are a convenient tool for modelling dependencies in competing risks models with multiple spells. This paper introduces several practical...
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Competing risks and multivariate outcomes in epidemiological and clinical trial research
Data analysis methods for the study of treatments or exposures in relation to a clinical outcome in the presence of competing risks have a long...