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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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Comparison of radiomic feature aggregation methods for patients with multiple tumors
Scientific Reports, 2021 Radiomic feature analysis has been shown to be effective at analyzing diagnostic images to model cancer outcomes. It has not yet been established how to best combine radiomic features in cancer patients with multifocal tumors.
Enoch Chang +7 more
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Trend-constrained corrected score for proportional hazards model with covariate measurement error
Contemporary Clinical Trials Communications, 2015 In many medical research studies, survival time is typically the primary outcome of interest. The Cox proportional hazards model is the most popular method to investigate the relationship between covariates and possibly right-censored survival time ...
Ming Zhu, Yijian Huang
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Proportional hazards models with continuous marks
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 this approach to allow a continuum of competing risks, in which the cause of failure is replaced by
Sun, Yanqing +2 more
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Comparison of methods for estimating the attributable risk in the context of survival analysis
BMC Medical Research Methodology, 2017 Background The attributable risk (AR) measures the proportion of disease cases that can be attributed to an exposure in the population. Several definitions and estimation methods have been proposed for survival data.
Malamine Gassama +3 more
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The importance of censoring in competing risks analysis of the subdistribution hazard
BMC Medical Research Methodology, 2017 Background The analysis of time-to-event data can be complicated by competing risks, which are events that alter the probability of, or completely preclude the occurrence of an event of interest.
Mark W. Donoghoe, Val Gebski
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Regression Models for Lifetime Data: An Overview
Stats, 2022 Two methods dominate the regression analysis of time-to-event data: the accelerated failure time model and the proportional hazards model. Broadly speaking, these predominate in reliability modelling and biomedical applications, respectively.
Chrys Caroni
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Combined oral contraceptive (COC) use in obese adult women dramatically increases the relative risk of developing a pulmonary embolism (PE). The risk of a PE in obese adolescent females taking contraceptives is currently unknown. The purpose of this investigation was to determine the effect of body mass index (BMI) and contraceptive
John Puetz, Joanne Salas
wiley +1 more source
Duration time‐series models with proportional hazard [PDF]
Journal of Time Series Analysis, 2007 Abstract. The analysis of liquidity in financial markets is generally performed by means of the dynamics of the observed intertrade durations (possibly weighted by price or volume). Various dynamic models for duration data have been considered in the literature, such as the Autoregressive Conditional Duration (ACD) model.
Patrick Gagliardini +1 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Central nervous system (CNS) neuroblastoma, FOXR2‐activated, is a recently recognized entity in the WHO CNS5 classification, defined by activation of the FOXR2 transcription factor and unique histopathological features. This review synthesizes available literature and pooled clinical data, providing insight into demographics ...
Sudarshawn Damodharan +1 more
wiley +1 more source