Results 121 to 130 of about 192,457 (154)

Semiparametric Models for Cumulative Incidence Functions

Biometrics, 2004
Summary.  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
James J Dignam
exaly   +4 more sources

Robust prediction of the cumulative incidence function under non‐proportional subdistribution hazards

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 ...
Qing Liu, Gong Tang, Joseph P Costantino   +2 more
exaly   +3 more sources

Prediction of Cumulative Incidence Function under the Proportional Hazards Model

Biometrics, 1998
In 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.
openaire   +3 more sources

Comparing k Cumulative Incidence Functions Through Resampling Methods

Lifetime Data Analysis, 2002
Tests 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
openaire   +5 more sources

Flexible parametric modelling of the cause‐specific cumulative incidence function

Statistics in Medicine, 2016
Competing 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., Wilkes, S. R., Crowther, Michael J.   +2 more
openaire   +4 more sources

Restricted estimation of the cumulative incidence functions of two competing risks

Journal of Statistical Planning and Inference, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Al-Kandari, Noriah, El Barmi, Hammou
openaire   +1 more source

Dynamic prediction of cumulative incidence functions by direct binomial regression

Biometrical Journal, 2018
AbstractIn 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., de Witte, T.J.M., de Witte, T.J.M., Putter, Hein   +3 more
openaire   +6 more sources

Two-sample tests of the equality of two cumulative incidence functions

Computational Statistics & Data Analysis, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ruta Bajorunaite, John P. Klein
openaire   +2 more sources

Comparing cumulative incidence functions of a competing-risks model

IEEE Transactions on Reliability, 1997
A 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
openaire   +1 more source