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Semiparametric analysis of competing risks data with covariate measurement error
This paper deals with the competing risks data with covariate measurement error. A semiparametric linear transformation model for the right-censored...
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Set-Based Tests for Genetic Association Studies with Interval-Censored Competing Risks Outcomes
Over the past decade, massive genetic compendiums such as the UK Biobank have gathered extensive genetic and phenotypic data that hold the potential...
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Marginal Structural Illness-Death Models for Semi-competing Risks Data
The three-state illness-death model has been established as a general approach for regression analysis of semi-competing risks data. For...
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A nonparametric instrumental approach to confounding in competing risks models
This paper discusses nonparametric identification and estimation of the causal effect of a treatment in the presence of confounding, competing risks...
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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...
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Semiparametric regression modelling of current status competing risks data: a Bayesian approach
The current status censoring takes place in survival analysis when the exact event times are not known, but each individual is monitored once for...
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A multinomial generalized linear mixed model for clustered competing risks data
Clustered competing risks data are a complex failure time data scheme. Its main characteristics are the cluster structure, which implies a latent...
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Use of Additional Information for Current Status Data with Two Competing Risks and Missing Failure Types
In practice, the failure type for some subjects may be missing or uncertain in competing risks data. Analysis of such uncertain failure type in...
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Inference for A Generalized Family of Distributions Under Partially Observed Left Truncated and Right Censored Competing Risks Data
We make inference for a competing risks model under the assumption that observations are left-truncated and right-censored and failure causes are...
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Model-based hypothesis tests for the causal mediation of semi-competing risks
Analyzing the causal mediation of semi-competing risks has become important in medical research. Semi-competing risks refers to a scenario wherein an...
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Bias reduction for semi-competing risks frailty model with rare events: application to a chronic kidney disease cohort study in South Korea
In a semi-competing risks model in which a terminal event censors a non-terminal event but not vice versa, the conventional method can predict...
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Inference of Competing Risks Model with Partially Observed Failure Causes Based on Minimum Ranked Set Sampling
Ranked set sampling (RSS) provides an efficient and flexible approach to collect failure information from perspectives of saving time and cost. In...
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Targeted maximum likelihood estimation for causal inference in survival and competing risks analysis
Targeted maximum likelihood estimation (TMLE) provides a general methodology for estimation of causal parameters in presence of high-dimensional...
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Causal survival analysis under competing risks using longitudinal modified treatment policies
Longitudinal modified treatment policies (LMTP) have been recently developed as a novel method to define and estimate causal parameters that depend...
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Inference of improved adaptive progressively censored competing risks data for Weibull lifetime models
Recently, an improved adaptive Type-II progressive censoring scheme is proposed to ensure that the experimental time will not pass a pre-fixed time...
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Phase-type models for competing risks, with emphasis on identifiability issues
We first review some main results for phase-type distributions, including a discussion of Coxian distributions and their canonical representations....
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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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Shared Frailty Model for Recurrent Event Competing Risks Data Using Averaged Counting Process Approach
In this paper, we present a shared frailty model for gap time distributions of recurrent event data with competing risks based on weighted risk-set...
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Semiparametric Model for Recurrent Event Data Under Two Independent Competing Risks with Excess Zero and Informative Censoring
Recurrent event data are often encountered in longitudinal studies and in many other important areas such as Biomedical science, Econometrics,...
