Smooth semi-nonparametric (SNP) estimation of the cumulative incidence function. [PDF]
Stat Med, 2017 This paper presents a novel approach to estimation of the cumulative incidence function in the presence of competing risks. The underlying statistical model is specified via a mixture factorization of the joint distribution of the event type and the time to the event.
Duc AN, Wolbers M.
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Nonparametric Estimation of Cumulative Incidence Functions of Recurrent Events
Statistica, 2023 The present paper discusses modeling and analysis of recurrent event data with competing risks. We propose non parametric estimation of cumulative incidence functions of recurrent event competing risks model.
Sisuma Mandakathingal Sivadasan +1 more
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Tests for Comparing Mark-Specific Hazards and Cumulative Incidence Functions [PDF]
Lifetime Data Analysis, 2004 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 observed at uncensored failure times. We develop nonparametric tests for this problem when the mark variable is continuous.
Peter Gilbert, Ian McKeague, Yanqing Sun
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Semiparametric regression on cumulative incidence function with interval-censored competing risks data. [PDF]
Stat Med, 2017 Many biomedical and clinical studies with time‐to‐event outcomes involve competing risks data. These data are frequently subject to interval censoring. This means that the failure time is not precisely observed but is only known to lie between two observation times such as clinical visits in a cohort study.
Bakoyannis G, Yu M, Yiannoutsos CT.
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Crude incidence in two-phase designs in the presence of competing risks [PDF]
BMC Medical Research Methodology, 2016 Background In many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies.
Paola Rebora +3 more
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Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms. [PDF]
Lifetime Data Anal, 2018 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 one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent.
Lok JJ, Yang S, Sharkey B, Hughes MD.
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Regression Analysis of Masked Competing Risks Data under Cumulative Incidence Function Framework
Austrian Journal of Statistics, 2020 In the studies that involve competing risks, somehow, masking issues might arise. That is, the cause of failure for some subjects is only known as a subset of possible causes.
Yosra Yousif +2 more
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Age-specific incidence of A/H1N1 2009 influenza infection in England from sequential antibody prevalence data using likelihood-based estimation. [PDF]
PLoS ONE, 2011 Estimating the age-specific incidence of an emerging pathogen is essential for understanding its severity and transmission dynamics. This paper describes a statistical method that uses likelihoods to estimate incidence from sequential serological data ...
Marc Baguelin +6 more
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Analyzing Competing Risk Data Using the R timereg Package [PDF]
Journal of Statistical Software, 2011 In this paper we describe flexible competing risks regression models using the comp.risk() function available in the timereg package for R based on Scheike et al. (2008).
Thomas H. Scheike, Mei-Jie Zhang
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Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases [PDF]
ARYA Atherosclerosis, 2014 BACKGROUND: Competing risks arise when the subject is exposed to more than one cause of failure. Data consists of the time that the subject failed and an indicator of which risk caused the subject to fail.
Minoo Dianatkhah +6 more
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