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Constrained parametric model for simultaneous inference of two cumulative incidence functions
Biometrical Journal, 2012We propose a parametric regression model for the cumulative incidence functions (CIFs) commonly used for competing risks data. The model adopts a modified logistic model as the baseline CIF and a generalized odds‐rate model for covariate effects, and it explicitly takes into account the constraint that a subject with any given prognostic factors should
Shi, Haiwen +2 more
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Non-parametric test of recurrent cumulative incidence functions for competing risks models
METRON, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sisuma, M. S., Sankaran, P. G.
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Two-Sample Tests Based on Cumulative Incidence Functions from Coherent Systems
Biometrika, 1993Summary: Suppose that \(n_ 1\) and \(n_ 2\) independent copies of a coherent system composed of \(m\) components operate in two different environments. All copies are monitored until their failure. The data consist of the lifetimes of all the components which fail before the system and the time to failure of the system which also is the censoring time ...
Deshpande, Jayant V. +2 more
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Confidence intervals for the cumulative incidence function via constrained NPMLE
Lifetime Data Analysis, 2018The cumulative incidence function (CIF) displays key information in the competing risks setting, which is common in medical research. In this article, we introduce two new methods to compute non-parametric confidence intervals for the CIF. First, we introduce non-parametric profile-likelihood confidence intervals.
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Canadian Journal of Statistics, 2016
AbstractPrediction of a cause‐specific cumulative incidence function (CIF) for data containing competing risks is of primary interest to clinicians when making treatment decisions for patients given their prognostic characteristics. The Fine–Gray regression model is widely used to incorporate multiple prognostic factors, yet it is not applicable when ...
Liu, Qing +3 more
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AbstractPrediction of a cause‐specific cumulative incidence function (CIF) for data containing competing risks is of primary interest to clinicians when making treatment decisions for patients given their prognostic characteristics. The Fine–Gray regression model is widely used to incorporate multiple prognostic factors, yet it is not applicable when ...
Liu, Qing +3 more
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Competing risks : modelling crude cumulative incidence functions
2005The clinical course of a disease is often characterized by the possible occurrence of several types of events, each one having a specific role for the evaluation of the therapeutical strategies. The event occurring as first is of particular interest, since it could be considered as ’’treatment failure’’ or ’’response to treatment’’.
P. Boracchi +3 more
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Two-sample tests of the equality of two cumulative incidence functions
Computational Statistics & Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bajorunaite, Ruta, Klein, John P.
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Estimating the Cumulative incidence Functions under Length-biased Sampling [PDF]
, 2004 Consider a population of individuals who experience K dierent causes of death.We observe the ones alive at time t0 and follow them until death or possiblecensoring time. Given this length biased sample, we introduce estimators ofthe cumulative incidence functions of "initial survival times" (i.e.
Jean-Yves Dauxois, Agathe Guilloux
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NON-PARAMETRIC INFERENCE FOR CUMULATIVE INCIDENCE FUNCTIONS IN COMPETING RISKS STUDIES
Statistics in Medicine, 1997In the competing risks problem, a useful quantity is the cumulative incidence function, which is the probability of occurrence by time t for a particular type of failure in the presence of other risks. The estimator of this function as given by Kalbfleisch and Prentice is consistent, and, properly normalized, converges weakly to a zero-mean Gaussian ...
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Lifetime Data Analysis, 2011
In the competing risks problem an important role is played by the cumulative incidence function (CIF), whose value at time t is the probability of failure by time t from a particular type of risk in the presence of other risks. Assume that the lifetime distributions of two populations are uniformly stochastically ordered.
Al-Kandari, Noriah M. A. +2 more
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In the competing risks problem an important role is played by the cumulative incidence function (CIF), whose value at time t is the probability of failure by time t from a particular type of risk in the presence of other risks. Assume that the lifetime distributions of two populations are uniformly stochastically ordered.
Al-Kandari, Noriah M. A. +2 more
openaire +3 more sources