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Semiparametric Models for Cumulative Incidence Functions
Biometrics, 2004Summary. In analyses of time‐to‐failure data with competing risks, cumulative incidence functions may be used to estimate the time‐dependent cumulative probability of failure due to specific causes. These functions are commonly estimated using nonparametric methods, but in cases where events due to the cause of primary interest are infrequent relative
Bryant, John, Dignam, James J.
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Two-sample tests of the equality of two cumulative incidence functions
Computational Statistics and Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
John P Klein
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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 ...
Roberta Ness, Qing Liu
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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 ...
Roberta Ness, Qing Liu
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Prediction of Cumulative Incidence Function under the Proportional Hazards Model
Biometrics, 1998In the presence of dependent competing risks in survival analysis, the Cox model can be utilized to examine the covariate effects on the cause-specific hazard function for the failure type of interest. For this situation, the cumulative incidence function provides an intuitively appealing summary curve for marginal probabilities of this particular ...
Cheng, S. C., Fine, Jason P., Wei, L. J.
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Comparing k Cumulative Incidence Functions Through Resampling Methods
Lifetime Data Analysis, 2002Tests for the equality of k cumulative incidence functions in a competing risks model are proposed. Test statistics are based on a vector of processes related to the cumulative incidence functions. Since their asymptotic distributions appear very complicated and depend on the underlying distribution of the data, two resampling techniques, namely the ...
Zhang, D, Zhu, L, Yuen, KC
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Flexible parametric modelling of the cause‐specific cumulative incidence function
Statistics in Medicine, 2016Competing risks arise with time‐to‐event data when individuals are at risk of more than one type of event and the occurrence of one event precludes the occurrence of all other events. A useful measure with competing risks is the cause‐specific cumulative incidence function (CIF), which gives the probability of experiencing a particular event as a ...
Lambert, Paul C. +2 more
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Restricted estimation of the cumulative incidence functions of two competing risks
Journal of Statistical Planning and Inference, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Al-Kandari, Noriah, El Barmi, Hammou
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Dynamic prediction of cumulative incidence functions by direct binomial regression
Biometrical Journal, 2018AbstractIn recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when ...
Grand, Mia K. +3 more
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Comparing cumulative incidence functions of a competing-risks model
IEEE Transactions on Reliability, 1997A competing-risks model refers to a situation where a system (or organism) is exposed to two or more causes of failure (or death) but its eventual failure (or death) can be attributed to exactly one of the causes of failure. The basic information available in the competing-risks situation is the time to failure of the system, and the corresponding ...
null Yanqing Sun, R.C. Tiwari
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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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