Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models [PDF]
Journal of Translational Medicine, 2021 Background The successful identification of breast cancer (BRCA) prognostic biomarkers is essential for the strategic interference of BRCA patients.
Lingyu Li, Zhi-Ping Liu
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Efficient Post-Shrinkage Estimation Strategies in High-Dimensional Cox’s Proportional Hazards Models [PDF]
EntropyRegularization methods such as LASSO, adaptive LASSO, Elastic-Net, and SCAD are widely employed for variable selection in statistical modeling. However, these methods primarily focus on variables with strong effects while often overlooking weaker signals,
Syed Ejaz Ahmed +2 more
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BHCox: Bayesian heredity-constrained Cox proportional hazards models for detecting gene-environment interactions [PDF]
BMC BioinformaticsBackground Gene-environment (G × E) interactions play a critical role in understanding the etiology of diseases and exploring the factors that affect disease prognosis.
Na Sun +6 more
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On hazard ratio estimators by proportional hazards models in matched-pair cohort studies [PDF]
Emerging Themes in Epidemiology, 2017 Background In matched-pair cohort studies with censored events, the hazard ratio (HR) may be of main interest. However, it is lesser known in epidemiologic literature that the partial maximum likelihood estimator of a common HR conditional on matched ...
Tomohiro Shinozaki +2 more
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Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models [PDF]
Frontiers in Psychology, 2016 Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and
Lois A Gelfand +3 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 +2 more
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The impact of violation of the proportional hazards assumption on the discrimination of the Cox proportional hazards model [PDF]
Diagnostic and Prognostic ResearchBackground The Cox proportional hazards regression model is frequently used to estimate an individual’s probability of experiencing an outcome within a specified prediction horizon. A key assumption of this model is that of proportional hazards.
Peter C. Austin, Daniele Giardiello
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Epidemiology, Biostatistics and Public HealthINTRODUCTION The Cox proportional hazards regression model is frequently used to develop clinical prediction models for time-to-event outcomes, allowing clinicians to estimate an individual’s risk of experiencing the outcome within specified time ...
Peter Austin, Daniele Giardiello
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Nonparametric Regression in Proportional Hazards Models
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 ...
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Pain and mortality among older adults in Korea [PDF]
Epidemiology and Health, 2021 OBJECTIVES With the increasing elderly population with chronic disease, understanding pain and designing appropriate policy interventions to it have become crucial.
Chiil Song, Wankyo Chung
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