Results 11 to 20 of about 192,913 (255)
Regression trees and ensembles for cumulative incidence functions [PDF]
Abstract The use of cumulative incidence functions for characterizing the risk of one type of event in the presence of others has become increasingly popular over the past two decades. The problems of modeling, estimation and inference have been treated using parametric, nonparametric and semi-parametric methods ...
Cho, Youngjoo +3 more
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Competing risks analysis of patients with Brain Stroke: a comparison of two different approaches
Objectives: Cumulative incidence function (CIF) measures the survival time of a particular hazard in the presence of others, while cause-specific (CS) one ignores the competing risks.
Solmaz Norouzi +4 more
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Background: In competing risks settings, the cause-specific cumulative incidence function is of great interest since it quantifies cumulative risk in the presence of other causes.
Daisuke Onozuka +3 more
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A competing risk analysis of colorectal cancer recurrence after curative surgery
Background This study examines the effect of prognostic patient and disease characteristics on colorectal cancer (CRC) recurrence after curative resection. We used competing risk analysis with death as a competing risk. This method provides the clinician
Angela E. Schellenberg +2 more
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Parametric regression on cumulative incidence function [PDF]
We propose parametric regression analysis of cumulative incidence function with competing risks data. A simple form of Gompertz distribution is used for the improper baseline subdistribution of the event of interest. Maximum likelihood inferences on regression parameters and associated cumulative incidence function are developed for parametric models ...
Jong-Hyeon, Jeong, Jason P, Fine
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In this paper we deal with the modelling of cumulative incidence function using improper Gompertz distribution based on middle censored competing risks survival data. Together with the unknown parameters, cumulative incidence function also estimated.
Habbiburr Rehman, Navin Chandra
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Revisiting the cumulative incidence function with competing risks data
AbstractWe consider estimation of the cumulative incidence function (CIF) in the competing risks Cox model. We study three methods. Methods 1 and 2 are existing methods while method 3 is a newly proposed method. Method 3 is constructed so that the sum of the CIF’s across all event types at the last observed event time is guaranteed, assuming no ties ...
David M Zucker, Malka Gorfine
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Weighted Competing Risks Quantile Regression Models and Variable Selection
The proportional subdistribution hazards (PSH) model is popularly used to deal with competing risks data. Censored quantile regression provides an important supplement as well as variable selection methods due to large numbers of irrelevant covariates in
Erqian Li +6 more
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Objectives: To explore the Cytomegalovirus (CMV) burden on the long-term post-transplant course in different donor ages, we evaluated the incidence and risk factors for CMV in our kidney-transplanted patients (KTs) with extensive adoption of expanded ...
Davide Diena +12 more
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Comparing center-specific cumulative incidence functions [PDF]
The competing risks data structure arises frequently in clinical and epidemiologic studies. In such settings, the cumulative incidence function is often used to describe the ultimate occurrence of a particular cause of interest. If the objective of the analysis is to compare subgroups of patients with respect to cumulative incidence, imbalance with ...
Fan, Ludi, Schaubel, Douglas E.
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