Results 221 to 230 of about 414,926 (263)

Adaptive Regression Splines in the Cox Model

Biometrics, 1999
Summary.We develop a method for constructing adaptive regression spline models for the exploration of survival data. The method combines Cox's (1972,Journal of the Royal Statistical Society, Series B34, 187–200) regression model with a weighted least‐squares version of the multivariate adaptive regression spline (MARS) technique of Friedman (1991 ...
LeBlanc, Michael, Crowley, John
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Diagnostic Plots in Cox's Regression Model

Biometrics, 1991
Two diagnostic plots are presented for validating the fitting of a Cox proportional hazards model. The added variable plot is developed to assess the effect of adding a covariate to the model. The constructed variable plot is applied to detect nonlinearity of a fitted covariate. Both plots are also useful for identifying influential observations on the
Chen, Chen-Hsin, Wang, P. C.
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Applying Cox Regression to Competing Risks

Biometrics, 1995
Two methods are given for the joint estimation of parameters in models for competing risks in survival analysis. In both cases Cox's proportional hazards regression model is fitted using a data duplication method. In principle either method can be used for any number of different failure types, assuming independent risks.
M, Lunn, D, McNeil
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Cox Regression with Covariate Measurement Error

Scandinavian Journal of Statistics, 2002
This article deals with parameter estimation in the Cox proportional hazards model when covariates are measured with error. We consider both the classical additive measurement error model and a more general model which represents the mis‐measured version of the covariate as an arbitrary linear function of the true covariate plus random noise.
Hu, Chengcheng, Lin, D. Y.
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On the interpretation of the hazard ratio in Cox regression

Biometrical Journal, 2019
AbstractWe argue that the term “relative risk” should not be used as a synonym for “hazard ratio” and encourage to use the probabilistic index as an alternative effect measure for Cox regression. The probabilistic index is the probability that the event time of an exposed or treated subject exceeds the event time of an unexposed or untreated subject ...
Jan De Neve, Thomas A. Gerds
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Predictive Accuracy and Explained Variation in Cox Regression

Biometrics, 2000
Summary.We suggest a new measure of the proportion of the variation of possibly censored survival times explained by a given proportional hazards model. The proposed measure, termedV, shares several favorable properties with an earlierV1but also improves the handling of censoring.
Schemper, M., Henderson, Robin
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Cox Regression Analysis in Clinical Research

Archives of Ophthalmology, 1990
The Cox survivorship model1has been used widely in medical research and recently in the ophthalmic literature to analyze prognosis following alternative treatments of uveal melanoma.2-5The purpose of this short communication is to explain what Cox regression analysis is, so that investigators will understand its role in clinical research.
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Cox Regressions

2023
Ton J. Cleophas, Aeilko H. Zwinderman
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Robust functional Cox regression model

Lifetime Data Analysis
Survival analysis with functional covariates has emerged as an important extension of the classical Cox proportional hazards model, allowing one to assess how entire trajectories or curves influence time-to-event outcomes. However, existing functional Cox models are typically fitted using non-robust techniques and can be highly sensitive to outliers or
Gizel Bakicierler Sezer, Ufuk Beyaztas
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Cox regression.

2022
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