Results 11 to 20 of about 355,313 (330)
On Cox proportional hazards model performance under different sampling schemes [PDF]
PLoS ONE, 2023 Cox’s proportional hazards model (PH) is an acceptable model for survival data analysis. This work investigates PH models’ performance under different efficient sampling schemes for analyzing time to event data (survival data). We will compare a modified
Hani Samawi, Lili Yu, JingJing Yin
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Proportional hazards models with continuous marks [PDF]
The Annals of Statistics, 2009 For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541--554]. This article studies an extension of
Gilbert, Peter B. +2 more
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Statistical estimation in the proportional hazards model with risk set sampling [PDF]
, 2004 Thomas' partial likelihood estimator of regression parameters is widely used in the analysis of nested case-control data with Cox's model. This paper proposes a new estimator of the regression parameters, which is consistent and asymptotically normal ...
Chen, Kani
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Quasi-linear Cox proportional hazards model with cross- L1 penalty [PDF]
BMC Medical Research Methodology, 2020 Background To accurately predict the response to treatment, we need a stable and effective risk score that can be calculated from patient characteristics.
Katsuhiro Omae, Shinto Eguchi
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Limitations of using COX proportional hazards model in cardiovascular research [PDF]
Cardiovascular DiabetologyThe article by Zhao et al. titled “Associations of Triglyceride-Glucose (TyG) Index with Chest Pain Incidence and Mortality among the U.S. Population” provides valuable insights into the positive correlation between the TyG index and chest pain incidence,
Nan Jiang, Yongfa Wu, Chengjia Li
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Two-Level Proportional Hazards Models [PDF]
Biometrics, 2002 We extend the proportional hazards model to a two-level model with a random intercept term and random coefficients. The parameters in the multilevel model are estimated by a combination of EM and Newton-Raphson algorithms. Even for samples of 50 groups, this method produces estimators of the fixed effects coefficients that are approximately unbiased ...
Maples, Jerry J. +2 more
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Explained randomness in proportional hazards models [PDF]
Statistics in Medicine, 2005 A coefficient of explained randomness, analogous to explained variation but for non-linear models, was presented by Kent. The construct hinges upon the notion of Kullback-Leibler information gain. Kent and O'Quigley developed these ideas, obtaining simple, multiple and partial coefficients for the situation of proportional hazards regression.
John O'Quigley, Janez Stare, Ronghui Xu
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Nonparametric Regression in Proportional Hazards Models [PDF]
JOURNAL OF THE JAPAN STATISTICAL SOCIETY, 2004 Summary: \textit{J. Fan} et al. [Ann. Stat. 25, No. 4, 1661--1690 (1997; Zbl 0890.62023)] considered two kinds of nonparametric estimators of the effects of the covariates in proportional hazards models. One of them has no parametric assumption on the baseline hazard function and is based on the integration of the estimated first order derivative of ...
Toshio Honda
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Optimal partitioning for the proportional hazards model. [PDF]
J Appl Stat, 2022 This paper discusses methods for clustering a continuous covariate in a survival analysis model. The advantages of using a categorical covariate defined from discretizing a continuous covariate (via clustering) is (i) enhanced interpretability of the covariate's impact on survival and (ii) relaxing model assumptions that are usually required for ...
Govindarajulu U, Tarpey T.
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Moving beyond the Cox proportional hazards model in survival data analysis: a cervical cancer study [PDF]
BMJ Open, 2020 Objectives This study explored the prognostic factors and developed a prediction model for Chinese-American (CA) cervical cancer (CC) patients. We compared two alternative models (the restricted mean survival time (RMST) model and the proportional ...
Lixian Li +3 more
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